U.S. patent application number 15/439192 was filed with the patent office on 2017-06-29 for method and system for evaluating sensor data from a well service rig.
This patent application is currently assigned to Key Energy Services, LLC. The applicant listed for this patent is Key Energy Services, LLC. Invention is credited to Lynn W. Conine, Derrek Yorga.
Application Number | 20170183954 15/439192 |
Document ID | / |
Family ID | 45991533 |
Filed Date | 2017-06-29 |
United States Patent
Application |
20170183954 |
Kind Code |
A1 |
Conine; Lynn W. ; et
al. |
June 29, 2017 |
Method And System For Evaluating Sensor Data From A Well Service
Rig
Abstract
As activities are completed at a well service rig, sensors
receive data and transmit it to a computer or database for storage.
The sensor data, including the time it takes to complete particular
activities on the rig, is evaluated to determine benchmarks. For
example, data from multiple instances of an activity is organized
and evaluated to determine the median value for data in that
activity. Outlier data is removed and the new median and moving
range is determined. A natural process limit range is then
determined based on the moving range and data for each instance is
compared to the natural process limit range. Instances that have
data outside of the natural process limit range are noted and go
through supplemental analysis to determine why the data was outside
of the natural process limit range. The data can also be evaluated
against activity benchmarks to determine if an activity was
completed properly.
Inventors: |
Conine; Lynn W.; (Houston,
TX) ; Yorga; Derrek; (Calgary, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Key Energy Services, LLC |
Houston |
TX |
US |
|
|
Assignee: |
Key Energy Services, LLC
Houston
TX
|
Family ID: |
45991533 |
Appl. No.: |
15/439192 |
Filed: |
February 22, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
13283473 |
Oct 27, 2011 |
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15439192 |
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61407427 |
Oct 27, 2010 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
E21B 47/00 20130101;
E21B 44/00 20130101 |
International
Class: |
E21B 47/00 20060101
E21B047/00 |
Claims
1. A computer-implemented method for evaluating data from a well
service rig comprising the steps of: receiving, at an at least one
analysis computer, a collection of data, wherein the collection of
data includes data for a plurality of instances of an activity
completed by a well service rig at a wellsite; conducting, with the
at least one analysis computer, a gross error review of the
collection of data; conducting, with the at least one analysis
computer, a tech limit activity review of the collection of data;
and generating, with the at least one analysis computer, a report
for the instances of the activity.
2. The method of claim 1, further comprising the steps of:
providing the well service rig at the wellsite; conducting an
instance of an activity with the well service rig; receiving a
plurality of data from a plurality of sensors at the wellsite while
conducting the instance of the activity; transmitting the plurality
of data to an area remote from the wellsite; and storing the
plurality of data for the instance of the activity in the data
storage device.
3. The method of claim 1, wherein the gross error review comprises
the steps of: sorting, with the at least one analysis computer, the
collection of data from a lowest value to a highest value;
determining, with the at least one analysis computer, a first
median data point for the collection of data; determining, with the
at least one analysis computer, a first median data value for the
collection of data; applying, with the at least one analysis
computer, a lower level boundary to the sorted collection of data
based on a first pre-programmed percentage; applying, with the at
least one analysis computer, an upper level boundary to the sorted
collection of data based on a second pre-programmed percentage; and
selecting, with the at least one analysis computer, all data points
in the sorted collection of data between the lower level boundary
and the upper level boundary.
4. The method of claim 1, wherein the first pre-programmed
percentage is within a first range between 15 percent and 35
percent and wherein the second pre-programmed percentage is within
a second range between 15 percent and 35 percent.
5. The method of claim 3, wherein the tech limit activity review of
the collection of data further comprises the steps of: sorting,
with the at least one analysis computer, the selected data in a
chronological order; determining, with the at least one analysis
computer, a second median data point for the selected,
chronologically ordered data; determining, with the at least one
analysis computer, a second median value for the selected,
chronologically ordered data; calculating, with the at least one
analysis computer, a moving range for the selected, chronologically
ordered data; calculating, with the at least one analysis computer,
a median of the moving range; and calculating an upper natural
process limit, with the at least one analysis computer, based on
the sum of the second median value and a product of a constant and
the median of the moving range; and comparing, with the at least
one analysis computer, data values for each instance of the
collection of data against the upper natural process limit, wherein
data values above the upper natural process limit are out of
range.
6. The method of claim 5, further comprising the steps of:
calculating a lower natural process limit, with the at least one
analysis computer, based on the difference of the second median
value and the product of a constant and the median of the moving
range; comparing, with the at least one analysis computer, data
values for each instance of the collection of data against the
lower natural process limit; and designating, with the at least one
analysis computer data values below the lower natural process limit
as out of range.
7. The method of claim 5, further comprising the steps of: adding
information about each instance of the activity with data out of
range to an out of range list; conducting additional analysis on
each instance of the activity on the out or range list;
8. The method of claim 1, further comprising the step of
determining, with the at least one analysis computer, a benchmark
for the activity based on tech limit activity review of the
collection of data.
9. The method of claim 1, further comprising the steps of:
determining, with the at least one analysis computer, if there is
another activity having data for a plurality of instances of the
another activity in the data storage device; and repeating the
steps of claim 1 for each additional activity.
10. A computer-implemented method for determining a trip activity
coefficient for an activity completed by a well service rig
comprising the steps of: receiving, at an at least one analysis
computer, a plurality of data for a single instance of the activity
completed by the well service rig; evaluating, with the at least
one analysis computer, a first portion of the plurality of data to
determine a gross time to complete the activity; evaluating, with
the at least one analysis computer, a third portion of the
plurality of data to determine a portion of the gross time the well
service rig conducted operations during the instance of the
activity and designating that portion of the gross time as a work
time; and calculating, with the at least one analysis computer, the
trip activity coefficient.
11. The method of claim 10, further comprising the steps of:
providing the well service rig at the wellsite; conducting the
instance of the activity with the well service rig; receiving the
plurality of data from a plurality of sensors at the wellsite while
conducting the instance of the activity; transmitting the plurality
of data to an area remote from the wellsite; and storing the
plurality of data for the instance of the activity in the data
storage device.
12. The method of claim 10, further comprising the steps of:
evaluating, with the at least one analysis computer, a second
portion of the plurality of data to determine an amount of wait
time occurring during the instance of the activity; calculating,
with the at least one analysis computer, the difference of the
gross time and the amount of wait time as a net time; and wherein
calculating the trip activity coefficient comprises calculating the
quotient of the work time divided by the net time.
13. The method of claim 12, further comprising the step of storing,
with the at least one analysis computer, the gross time, wait time,
net time, work time and trip activity coefficient for the instance
of the activity in the data storage device.
14. The method of claim 10, wherein calculating the trip activity
coefficient comprises calculating the quotient of the work time
divided by the gross time.
15. The method of claim 10, further comprising the step of
calculating, with the at least one analysis computer, a total
number of tubing joints run during the instance of the
activity.
16. The method of claim 15, wherein calculating the total number of
tubing joints comprises the steps of: receiving, at the at least
one analysis computer, a plurality of tripping data comprising a
plurality of trips of running tubing into or out of the well;
determining a joint length for each tubing joint run into or out of
the well for each trip, receiving, at the at least one analysis
computer, a first data value representing a minimum block position
sensed during the trip; for each trip, receiving, at the at least
one analysis computer, a second data value representing a maximum
block position sensed during the trip; for each trip, calculating,
at the at least one analysis computer, a difference between the
second data value and the first data value as a block movement
value; for each trip, calculating to a nearest integer, at the at
least one analysis computer, a quotient of the block movement value
divided by the joint length as a tubing joint count for the trip;
and calculating as a total tubing joint value, at the at least one
analysis computer, a sum of the tubing joint count for the
plurality of trips.
17. The method of claim 16, further comprising the steps of: for
each trip, receiving, at the at least one analysis computer, a
third data value representing a maximum load sensed during the
trip; for each trip, receiving, at the at least one analysis
computer, a fourth data value representing a minimum load sensed
during the trip; for each trip, receiving, at the at least one
analysis computer, a fifth data value representing a maximum
pressure for a tongs during the trip; for each trip, comparing, at
the at least one analysis computer, a difference between the third
data value and the fourth data value is greater than a load
threshold value; for each trip, determining, at the at least one
analysis computer, if the fifth data value is greater than a
pressure threshold value; and for each trip, determining, with the
at least one analysis computer, that zero tubing joints were run
into or pulled out of the well if the difference between the third
data value and the fourth data value is not greater than the load
threshold value and if the fifth data value is not greater than the
pressure threshold value.
18. The method of claim 17, wherein the load threshold value is
between one hundred pounds and ten thousand pounds.
19. The method of claim 17, wherein the pressure threshold value is
between one hundred and nine hundred pounds per square inch.
20. A computer-implemented method for determining if a tubing
anchor was set properly by a well service rig comprising the steps
of: a. receiving, at an at least one analysis computer, a plurality
of load data collected during an instance of setting the tubing
anchor with the well service rig; b. receiving, an the at least one
analysis computer, a plurality of block position data collected
during the instance; c. evaluating, with the at least one analysis
computer, the plurality of load data to determine if there is a
first portion of the plurality of load data that increases to a
string weight; d. evaluating, with the at least one analysis
computer, the plurality of block position data to identify a first
period where a first portion of the plurality of block position
data identifies that a block is moving upward; e. evaluating, with
the at least one analysis computer, the plurality of load data to
determine if during the first period, a load represented by the
load data increases a first nominal amount; f. evaluating, with the
at least one analysis computer, the plurality of block position
data to determine if a second period exists after the first period
where a second portion of the plurality of block position data
identifies that the block is moving downward; g. evaluating, with
the at least one analysis computer, the plurality of load data to
determine if during the second period, the load represented by the
load data decreases a second nominal amount; h. evaluating, with
the at least one analysis computer, the plurality of block position
data to determine if a third period exists after the second period
where a third portion of the plurality of block position data
identifies that the block is moving upward; i. evaluating, with the
at least one analysis computer, the plurality of load data to
determine if during the third period, the load represented by the
load data increases a third nominal amount; j. evaluating, with the
at least one analysis computer, the plurality of block position
data to determine if a fourth period exists after the third period
where a fourth portion of the plurality of block position data
identifies that the block is moving downward; k. evaluating, with
the at least one analysis computer, the plurality of load data to
determine if during the fourth period, the load represented by the
load data decreases a fourth nominal amount; l. evaluating, with
the at least one analysis computer, the plurality of block position
data and the plurality of load data to determine if a fifth period
exists after the fourth period where a fifth portion of the
plurality of block position data and a fifth portion of the
plurality of load data are substantially stable for a predetermined
amount of time; and m. generating a positive notification that the
tubing anchor was set properly based on a positive determination in
steps c-1.
21. The method of claim 20, wherein the predetermined amount of
time is at least three minutes.
22. The method of claim 20, wherein the first nominal amount,
second nominal amount, third nominal amount, and fourth nominal
amount are each between 1500 pounds and 80,000 pounds.
Description
RELATED PATENT APPLICATION
[0001] This application is a divisional application of and claims
priority under 35 U.S.C. .sctn.120 to U.S. Nonprovisional patent
application Ser. No. 13/283,473, filed Oct. 27, 2011, and titled
"Method and System for Evaluating Sensor Data From a Well Service
Rig," which claims priority under 35 U.S.C. .sctn.119 to U.S.
Provisional Patent Application Ser. No. 61/407,427, filed Oct. 27,
2010, and titled "Methods of Evaluating Sensor Data From a Well
Service Rig and Calculating Upper and Lower Operating Limits for
Activity Data from a Well Service Rig," the entire contents of both
which are hereby incorporated herein by reference herein for all
purposes.
TECHNICAL FIELD
[0002] The present disclosure relates generally to evaluation of
sensor data concerning servicing hydrocarbon wells and more
specifically to an evaluation of sensor data obtained from a
computerized work over rig adapted to record and transmit sensor
data concerning well servicing activities and conditions at a well
site.
BACKGROUND
[0003] After drilling a hole through a subsurface formation and
determining that the formation can yield an economically sufficient
amount of oil or gas a crew completes the well. Once completed, a
variety of events may occur to the formation causing the well and
its equipment to require a "work-over." For purposes of this
application, "work-over" and "service" operations are used in their
very broadest sense to refer to all activities performed on or for
a well to repair or rehabilitate the well, and also includes
activities to shut in or cap the well. Generally, workover
operations include such things as replacing worn or damaged parts
(e.g., a pump, sucker rods, tubing, and packer glands), applying
secondary or tertiary recovery techniques, such as chemical or hot
oil treatments, cementing the wellbore, and logging the wellbore,
to name just a few.
[0004] During drilling, completion, and well servicing, personnel
routinely insert into and/or extract equipment such as tubing,
tubes, pipes, rods, hollow cylinders, casing, conduit, collars, and
duct from the well. For example, a service crew may use a workover
or service rig (collectively hereinafter "service rig" or "rig")
that is adapted to complete a number of activities at the well,
including, but not limited to, pulling the well tubing or rods out
of the well, setting tubing anchors, and also to run the tubing or
rods back into the well. Typically, these mobile service rigs are
motor vehicle-based and have an extendible, jack-up derrick
complete with draw works and block and have numerous sensors that
receive data as the activities are being completed at the well. In
most cases the data from these sensors and other input devices are
recorded and stored in case they need to be subsequently evaluated.
Over time, a significant amount of data for numerous instances of
an activity completed on different rigs and by different work crews
is collected. Finding ways to use that data to improve operations,
evaluating whether activities are being completed properly and
improve safety for the rig crew would improve the overall operation
of the rig as it completes the activities in the future.
SUMMARY
[0005] The exemplary embodiments described herein describe systems
and methods for evaluating sensor, time and activity data obtained
by a well service rig or vehicle while it is conducting activities
near a well and using that evaluation of data to, for example,
determine if the activity was completed properly, set benchmarks
based on an evaluation of numerous activities and compare data to
the benchmarks to determine instances of activities that are
outside a natural process limits for that particular benchmark. For
one aspect of the present invention, a computer-implemented method
for evaluating data from a well service rig can include the step of
receiving a collection of data, wherein the collection of data
includes data for multiple instances of an activity completed by a
well service rig at a wellsite. The method can also include the
step of conducting a gross error review of the collection of data.
In addition, the method can include the step of conducting a tech
limit activity review of the collection of data. Furthermore, the
exemplary method can include the step of generating a report for
the instances of the activity.
[0006] For another aspect of the present invention, a
computer-implemented method for determining a trip activity
coefficient for an activity completed by a well service rig can
include the step of receiving, a multiple data entries for a single
instance of the activity completed by the well service rig. The
method can also include the step of evaluating a first portion of
the multiple data entries to determine a gross time or total time
to complete the activity. The method can also include the step of
evaluating another portion of the multiple data entries to
determine a portion of the gross time that the well service rig
conducted operations during the instance of the activity and can
designate that portion of the gross time as work time. In addition,
the exemplary method can include the step of calculating the trip
activity coefficient for that instance of the activity.
[0007] For yet another aspect of the present invention, a
computer-implemented method for determining if a tubing anchor was
set properly by a well service rig can include the step of
receiving multiple entries of load data collected during an
instance of setting the tubing anchor with the well service rig.
The method can also include the step of receiving multiple entries
of block position data collected during the instance. The method
can also include the step of evaluating the multiple entries of
load data to determine if there is a first portion of the load data
that increases to a string weight. In addition, the exemplary
method can include the step of evaluating the multiple entries of
block position data to identify a first period where a first
portion of the block position data shows that a block is moving
upward. Also, the exemplary method can include the step of
evaluating the load data to determine if during the first period,
the load increases a first nominal amount. Further, the exemplary
method can include the step of evaluating the block position data
to determine if a second period exists after the first period where
a second portion of the block position data shows that the block is
moving downward. The method can also include the step of evaluating
the load data to determine if during the second period, the load
decreases a second nominal amount. In addition, the method can
include the step of evaluating the block position data to determine
if a third period exists after the second period where a portion of
the block position data shows that the block is moving upward.
Further, the method can include the step of evaluating the load
data to determine if during the third period, the load increases a
third nominal amount. Also, the method can include the step of
evaluating the block position data to determine if a fourth period
exists after the third period where a portion of the block position
data shows that the block is moving downward. The method can also
include the step of evaluating the load data to determine if during
the fourth period, the load decreases a fourth nominal amount. In
addition, the method can include the step of evaluating the block
position data and the load data to determine if a fifth period
exists after the fourth period where a fifth portion of the block
position data and the load data are substantially stable for a
predetermined amount of time. Further, the method can include the
step of generating a positive notification that the tubing anchor
was set properly based on a positive determination in the
determining steps.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] Reference will now be made to the accompanying drawings,
which are not necessarily drawn to scale, and wherein:
[0009] FIG. 1 is a side view of an exemplary mobile repair unit
with its derrick extended according to one exemplary
embodiment;
[0010] FIG. 2 is a side view of the exemplary mobile repair unit
with its derrick retracted according to one exemplary
embodiment;
[0011] FIG. 3 is an electrical schematic of a monitor circuit
according to one exemplary embodiment;
[0012] FIG. 4 illustrates the raising and lowering of an inner
tubing string with an exemplary mobile repair unit according to one
exemplary embodiment;
[0013] FIG. 5 illustrates one embodiment of an activity capture
methodology outlined in tabular form according to one exemplary
embodiment;
[0014] FIG. 6 provides a frontal view of an exemplary operator
interface according to one exemplary embodiment;
[0015] FIG. 7 is a schematic diagram of an exemplary data
management system according to one exemplary embodiment;
[0016] FIG. 8 is a flow chart presenting a method for evaluating
sensor and activity data according to one exemplary embodiment;
[0017] FIG. 9 is a flow chart presenting a method for gross error
review of sensor data and activity data in accordance with one
exemplary embodiment;
[0018] FIG. 10 is a flow chart presenting a method for tech limit
activity review of sensor data and activity data in accordance with
one exemplary embodiment;
[0019] FIG. 11 is a flow chart presenting a method for conducting
additional analysis of sensor data and activity data in accordance
with one exemplary embodiment;
[0020] FIG. 12 is a flow chart presenting a method for conducting
data mining of sensor data and activity data in accordance with one
exemplary embodiment;
[0021] FIG. 13 is a flow chart presenting a method for determining
the number of stands pulled out of or run into a whole during an
activity in accordance with one exemplary embodiment;
[0022] FIG. 14 is a flow chart presenting a method for verifying
that a tubing anchor catcher was set correctly in accordance with
one exemplary embodiment;
[0023] FIG. 15 is a table presenting an example of the steps in the
gross error review and tech limit activity review of FIG. 9 for
representative data in accordance with one exemplary
embodiment;
[0024] FIG. 16 is a table presenting certain exemplary calculations
from the gross error review and tech limit activity review of FIG.
15 in accordance with one exemplary embodiment;
[0025] FIG. 17 is a table presenting an exemplary calculation of
median for data in the gross error review and tech limit activity
review of FIG. 15 in accordance with one exemplary embodiment of
the present invention;
[0026] FIG. 18 is a representative job efficiency report in
accordance with one exemplary embodiment of the present invention;
and
[0027] FIGS. 19A-C are a representative job summary report in
accordance with one exemplary embodiment of the present
invention.
[0028] The drawings illustrate only exemplary embodiments of the
invention and are therefore not to be considered limiting of its
scope, as the invention may admit to other equally effective
embodiments. The elements and features shown in the drawings are
not necessarily to scale, emphasis instead being placed upon
clearly illustrating the principles of the exemplary embodiments.
Additionally, certain dimensions or positionings may be exaggerated
to help visually convey such principles. In the drawings, reference
numerals designate like or corresponding, but not necessarily
identical, elements.
DETAILED DESCRIPTION OF THE EXEMPLARY EMBODIMENTS
[0029] Exemplary embodiments will now be described in detail with
reference to the included figures. The exemplary embodiments are
described in reference to how they might be implemented. In the
interest of clarity, not all features of an actual implementation
are described in this specification. Those of ordinary skill in the
art will appreciate that in the development of an actual
embodiment, several implementation-specific decisions must be made
to achieve the inventors' specific goals, such as compliance with
system-related and business-related constraints which can vary from
one implementation to another. Moreover, it will be appreciated
that such a development effort might be complex and time-consuming,
but would nevertheless be a routine undertaking for those of
ordinary skill in the art having benefit of this disclosure.
Further aspects and advantages of the various figures of the
invention will become apparent from consideration of the following
description and review of the figures. While references are
generally made hereinafter to rods, tubing, or casing specifically,
with the description of the figures, each reference should be read
broadly to include rods, tubing, casing, piping, and other downhole
equipment unless specifically limited therein.
[0030] The exemplary embodiments are also directed to retrieval and
evaluation of sensor data obtained during activities at a workover
or well-service rig and, in certain embodiments, calculating upper
and lower limits for activity data derived from the workover or
well-service rig (collectively the "well-service rig" or "rig").
The exemplary embodiments support computer-implemented methods and
systems for the retrieval and analysis of the sensor data, time
data, and activity data from the well-service rig in a networked or
stand-along computing system. Furthermore the exemplary system, or
portions thereof, can be located at or adjacent to the well-service
rig or at a location remote from the well-service rig, such as a
shop, business office or business headquarters.
[0031] In a distributed computing environment, program modules and
the sensor data obtained from the well-service rig may be
physically located in different local and remote memory storage
devices or databases. Execution of the program modules may occur
locally in a stand-alone manner or remotely in a client/server
manner. Examples of such distributed computing environments include
local area networks, enterprise wide computer networks, and the
global Internet.
[0032] The detailed description that follows is represented largely
in terms of processes and symbolic representations of operations by
conventional computing components, including processing units,
memory storage devices, databases, display devices, and input
devices. These processes and operations may utilize conventional
computer components in a stand-alone or distributed computing
environment.
[0033] The processes and operations performed by the computer
include the manipulation of signals by a processing unit or remote
computer and the maintenance of these signals within data
structures resident in one or more of the local or remote memory
storage devices. Such data structures impose a physical
organization upon the collection of data stored within a memory
storage device and represent specific, electrical or magnetic
elements. The symbolic representations are the means used by those
skilled in the art of computer programming and computer
construction to most effectively convey teachings and discoveries
to others skilled in the art.
[0034] Exemplary embodiments of the present invention include a
computer program that embodies the functions described herein and
illustrated in the flowcharts. However, it should be apparent that
there could be many different ways of implementing the invention in
computer programming, and the invention should not be construed as
limited to any one set of the computer program instructions.
Furthermore, a skilled programmer would be able to write such a
computer program to implement a disclosed embodiment of the present
invention without difficulty based, for example, on the tables and
flowcharts and associated description in the application text.
Therefore, disclosure or a particular set of program code
instructions is not considered necessary for an adequate
understanding of how to make and use the present invention.
[0035] Referring to FIG. 1, a retractable, self-contained mobile
repair unit 20 is presented to include a truck frame 22 supported
on wheels 24, an engine 26, a hydraulic pump 28, an air compressor
30, a first transmission 32, a second transmission 34, a variable
speed hoist 36, a block 38, an extendible derrick 40, a first
hydraulic cylinder 42, a second hydraulic cylinder 44, a first
transducer 46, a monitor 48, and retractable feet 50.
[0036] The engine 26 selectively couples to the wheels 24 and the
hoist 36 by way of the transmissions 34 and 32, respectively. The
engine 26 also drives the hydraulic pump 28 via the line 29 and the
air compressor 30 via the line 31. The compressor 30 powers a
pneumatic slip (Not Shown), and the pump 28 powers a set of
hydraulic tongs (Not Shown). The pump 28 also powers the cylinders
42 and 44 which respectively extend and pivot the derrick 40 to
selectively place the derrick 40 in a working position, as shown in
FIG. 1, and in a lowered position, as shown in FIG. 2. In the
working position, the derrick 40 is pointed upward, but its
longitudinal centerline 54 is angularly offset from vertical as
indicated by the angle 56. The angular offset provides the block 38
access to a wellbore 58 without interference with the derrick pivot
point 60. With the angular offset 56, the derrick framework does
not interfere with the typically rapid installation and removal of
numerous inner pipe segments (known as pipe, inner pipe string,
rods, or tubing 62, hereinafter interchangeably referred to in a
non-limiting manner as "tubing" or "rods").
[0037] Individual pipe segments (of string 62 in FIG. 4) and sucker
rods are screwed to themselves using hydraulic tongs. The term
"hydraulic tongs" used herein and below refer to any hydraulic tool
that can screw together two pipes or sucker rods. In operation, the
pump 28 drives a hydraulic motor (Not Shown) forward and reverse by
way of a valve. Conceptually, the motor drives the pinions which
turn a wrench element relative to a clamp. The element and clamp
engage flats on the mating couplings of a sucker rod or an inner
pipe string 62 of one conceived embodiment of the invention.
However, it is well within the scope of the invention to have
rotational jaws or grippers that clamp on to a round pipe (i.e., no
flats) similar in concept to a conventional pipe wrench, but with
hydraulic clamping. The rotational direction of the motor
determines assembly or disassembly of the couplings.
[0038] While not explicitly shown in the figures, when installing
the tubing segments 62, the pneumatic slip is used to hold the
tubing 62 while the next segment of tubing 62 is screwed on using
tongs. A compressor 30 provides pressurized air through a valve to
rapidly clamp and release the slip. A tank helps maintain a
constant air pressure. Pressure switch provides the monitor 48
(FIG. 3) with a signal that indirectly indicates that the rig 20 is
in operation.
[0039] Referring back to FIG. 1, weight applied to the block 38 is
sensed by way of a hydraulic pad 92 that supports the weight of the
derrick 40. The hydraulic pad 92 is basically a piston within a
cylinder (alternatively a diaphragm). Hydraulic pressure in the pad
92 increases with increasing weight on the block 38. In FIG. 3, the
first transducer 46 converts the hydraulic pressure to a 0-5 VDC
signal 94 that is conveyed to the monitor 48. The monitor 48
converts signal 94 to a digital value, stores it in a memory 96,
associates it with a real time stamp, and eventually communicates
the data to a remote computer 100 or the computer 605, of FIG. 6,
by way of hardwire, a modem 98, T1 line, WiFi, satellite, portable
data storage means, such as compact disc (CD), dongle, digital
video disc (DVD), tape drive, portable hard drive, disc or other
device or method for transferring data known to those of ordinary
skill in the art.
[0040] Returning to FIG. 3, transducers 46 and 102 are shown
coupled to the monitor 48. The transducer 46 indicates the pressure
on the left pad 92 and the transducer 102 indicates the pressure on
the right pad 92. A generator 118 driven by the engine 26 provides
an output voltage proportional to the engine speed. This output
voltage is applied across a dual-resistor voltage divider to
provide a 0-5 VDC signal at point 120 and then passes through an
amplifier 122. A generator 118 represents just one of many various
tachometers that provide a feedback signal proportional to the
engine speed. Another example of a tachometer would be to have
engine 26 drive an alternator and measure its frequency. The
transducer 80 provides a signal proportional to the pressure of
hydraulic pump 28, and thus proportional to the torque of the
tongs.
[0041] A telephone accessible circuit 124, referred to as a "POCKET
LOGGER" by Pace Scientific, Inc. of Charlotte, N.C., includes four
input channels 126, 128, 130 and 132; a memory 96 and a clock 134.
The circuit 124 periodically samples inputs 126, 128, 130 and 132
at a user selectable sampling rate; digitizes the readings; stores
the digitized values; and stores the time of day that the inputs
were sampled. It should be appreciated by those skilled in the art
that with the appropriate circuit, any number of inputs can be
sampled and the data could be transmitted instantaneously upon
receipt.
[0042] A supervisor at a computer 100 remote from or adjacent to
the work site at which the service rig 20 is operating accesses the
data stored in the circuit 124 by way of a PC-based modem 98 or
cable modem and a cellular phone 136, satellite, WiFi or other
known methods for wired or wireless data transfer. The phone 136
reads the data stored in the circuit 124 via the lines 138 (RJ11
telephone industry standard) and transmits the data to the modem 98
by way of antennas 140 and 142.
[0043] The amplifiers 122, 144, 146 and 148 condition their input
signals to provide corresponding inputs 126, 128, 130 and 132
having an appropriate power and amplitude range. Sufficient power
is needed for RC circuits 150 which briefly (e.g., 2-10 seconds)
sustain the amplitude of inputs 126, 128, 130 and 132 even after
the outputs from transducers 46, 102 and 80 and the output of the
generator 118 drop off. This ensures the capturing of brief spikes
without having to sample and store an excessive amount of data. A
DC power supply 152 provides a clean and precise excitation voltage
to the transducers 46, 102 and 80; and also supplies the circuit
124 with an appropriate voltage by way of a voltage divider 154. A
pressure switch 90 enables the power supply 152 by way of the relay
156, whose contacts 158 are closed by the coil 160 being energized
by the battery 162. FIG. 4 presents an exemplary display
representing a service rig 20 lowering an inner pipe string 62 as
represented by arrow 174 of FIG. 4.
[0044] FIG. 5 provides an illustration of an activity capture
methodology in tabular form according to one exemplary embodiment
of the present invention. Now referring to FIG. 5, an operator
first chooses an activity identifier for his/her upcoming task. If
"GLOBAL" is chosen, then the operator would choose from rig
up/down, pull/run tubing or rods, or laydown/pickup tubing and rods
(options not shown in FIG. 6). If "ROUTINE: INTERNAL" is selected,
then the operator would choose from rigging up or rigging down an
auxiliary service unit, longstroke, cut paraffin, nipple up/down a
BOP, fishing, jarring, swabbing, flowback, drilling, clean out,
well control activities such as killing the well or circulating
fluid, unseating pumps, set/release tubing anchor, set/release
packer, and pick up/laydown drill collars and/or other tools.
Finally, if "ROUTINE: EXTERNAL" is chosen, the operator would then
select an activity that is being performed by a third party, such
as rigging up/down third party servicing equipment, well
stimulation, cementing, logging, perforating, or inspecting the
well, and other common third party servicing tasks. After the
activity is identified, it is classified. For all classifications
other than "ON TASK: ROUTINE," a variance identifier is selected,
and then classified using the variance classification values.
[0045] FIG. 6 provides a view of an rig operator interface or
supervisor interface according to one exemplary embodiment of the
present invention. Now referring to FIG. 6, all that is required
from the operator is that he or she input in the activity data into
a computer 605. The operator can interface with the computer 605
using a variety of means, including typing on a keyboard 625 or
using a touch-screen 610. In one embodiment, a touch-screen display
610 with pre-programmed buttons, such as pulling rods or tubing
from a wellbore 615, is provided to the operator, as shown in FIG.
6, which allows the operator to simply select the activity from a
group of pre-programmed buttons. For instance, if the operator were
presented with the display 610 of FIG. 6 upon arriving at the well
site, the operator would first press the "RIG UP" button. The
operator would then be presented with the option to select, for
example, "SERVICE UNIT," "AUXILIARY SERVICE UNIT," or "THIRD
PARTY." The operator then would select whether the activity was on
task, or if there was an exception, such as WAIT TIME or MACHINE
DOWN, as described above. In addition, as shown in FIG. 6, prior to
pulling (removing) 615 or running (inserting) rods 62, the operator
could set the high and low limits for the block 38 by pressing the
learn high or learn low buttons after moving the block 38 into the
proper position.
[0046] FIG. 7 is a schematic diagram of an exemplary data
management system 700 for receiving and evaluating data received
from sensors and from the rig 20 according to one exemplary
embodiment. Referring now to FIGS. 1-7, the data management system
700 includes data that is received from the sensors 38, 46, 102,
80, 118 and any other sensors on the rig 20 or used during an
activity with the rig 20, even if not physically connected to the
rig 20. Other data, including but not limited to, timing data for
each activity from the clock 134 or other operational or activity
data from the rig 20 is also acquired and transmitted by the system
700. The data is transmitted from the rig 20 or from a device near
the rig to a database 705 and/or the computer 100 for storage and
evaluation of the data. The data can also be transmitted to the
display 610 of the computer 605 for evaluation by the rig operator.
In one exemplary embodiment, the data is transmitted with a modem
98. Alternatively, the data can be wired or wirelessly communicated
to the computer 605, database 705 and/or computer 100 by way of
electrical cable, WiFi, satellite transmission, cellular
transmission or any other means of data transmission known to those
of ordinary skill in the art. While not shown in FIG. 7, the rig 20
can also include a device, such as a database, dongle, compact disc
drive, DVD drive or similar means for recording and storing the
data at the rig 20. In addition, while the exemplary embodiment
describes the system having one analysis computer 100 for receiving
and analyzing the data, the system 700 can alternatively include
multiple general purpose computers or multiple general purpose
processors within a computer, set of computers or mainframe system
for receiving and analyzing the data from the sensors.
[0047] FIG. 8 is a flow chart presenting a method for evaluating
sensor and activity data according to one exemplary embodiment.
Referring now to FIGS. 1-8, the exemplary method 800 begins at the
START step and proceeds to step 805, where an activity is conducted
at the wellsite. The activity is typically conducted with the rig
20 and sensors (such as those described in FIG. 7) record data
during the activity and the clock 134 records the time to complete
the activity. In one exemplary embodiment, the well-service rig 20
can be as substantially described in U.S. Pat. Nos. 6,079,490 (the
"'490 Patent") and U.S. Pat. No. 7,006,920 (the "'920 Patent"), the
entire contents of which are hereby incorporated herein by
reference. The activities can include any activity typically
accomplished with a well-service rig, including, but not limited
to, rig up service unit, kill well, pull out of the hole rods, pick
up tubing, lay down tubing, pull out of hole tubing while scanning,
run in hole tubing while hydro testing, pick up rods, lay down
rods, pull out of the hole tubing, nipple-up blow out preventer
(BOP), run in the hole rods, run in the hole tubing, set tubing
anchor catcher, rig down the service unit.
[0048] In step 810, the sensor data and time data (which can
include one or more types of sensor data obtained by sensors on or
electrically coupled or associated with the well-service rig 20) is
received at the display while the activity is being conducted at
the wellsite by the rig 20. The sensor and time data is transmitted
or transported (when stored on a physically transportable storage
medium using, for example, a memory stick, hard drive, portable
hard drive, CD, DVD, dongle or the like) to the analysis computer
100 or "portal" or the database 705 in step 815. The terms analysis
computer 100 and portal will be used interchangeably herein. In one
exemplary embodiment, the sensor and time data are transmitted from
the rig 20 by the modem 98 to the database 705 and subsequently
provided to the analysis computer 100, which is communicably
coupled to the database 705. Alternatively, the sensor and time
data are transmitted by wired or other wireless communication from
the rig 20 to the database 705 or analysis computer 100.
[0049] In step 820, the analysis computer 100 receives the sensor
or time data for the particular instance of the activity and
receives similar sensor or time data for additional instances of
the activity from the database 705. In one exemplary embodiment,
the activity sensor data or time data for multiple instances of the
activity have been collected from multiple well-service rigs
conducting this activity at multiple wellsites and by multiple
crews and is stored in the database 705, or other memory storage
device known to those of ordinary skill in the art, until it is
analyzed and evaluated by the analysis computer 100. In certain
exemplary embodiments, the retrieval and analysis of multiple
instances of the activity are alternatively described with regards
to the method of data mining described in greater detail in FIG. 12
below. In one exemplary embodiment, the data received at the
analysis computer 100 for the multiple instances of a particular
activity is data representing the amount of time it took to
complete that instance of the activity. Alternatively, other sensor
data for each instance of an activity is received an analyzed by
the analysis computer 100. Further, in certain exemplary
embodiments, the analysis is completed on multiple instances of
each particular activity or sub-activity completed by the rig crew
at the wellsite.
[0050] In step 825, a gross error review of the data for the
multiple instances of the particular activity being evaluated is
completed. In one exemplary embodiment, the gross error review is
completed by the analysis computer 100. A tech limit activity
review of the data for the multiple instances of the particular
activity is completed in step 830. In one exemplary embodiment, the
tech limit activity review is completed by the analysis computer
100. In step 835, data mining for particular data related to one or
more activities is completed in step 835. In one exemplary
embodiment, the data mining is completed by the analysis computer
100, which retrieves and analyzes the data being stored in the
database 705. Benchmarks and metrics for quality and quantitative
improvements based on the analysis conducted in steps 825-835 for
the particular activity based on the received data are determined
in step 840. In certain exemplary embodiments, the benchmarks are
determined by the analysis computer 100. The process is iterative
in that the process will repeat for each activity and sub-activity
for which activity data is recorded at the well service rig 20 and
the data, scorecards, and reports can be updated on a daily,
weekly, monthly or more or less frequent basis depending on the
desires of the party implementing the exemplary system and
methods
[0051] In step 845, an inquiry is conducted to determine if there
is another activity on which to conduct an analysis of sensor or
time data. The determination can be made by the analysis computer
100 evaluating the types of activities being completed by the rig
20 or the types of activity for which sensor or time data is stored
in the database 705 or within the internal storage of the computer
100. If there is another activity to evaluate, the YES branch is
followed to step 820, where the analysis computer 100 receives the
sensor or time data for the next activity. Otherwise, the NO branch
is followed to the END step.
[0052] FIG. 9 is a flow chart presenting a method 825 for
conducting gross error review of sensor or time data for an
activity according to one exemplary embodiment. FIG. 15 is a table
presenting an example of the steps in FIGS. 9 and 10. Now referring
to FIGS. 1-9 and 15, the exemplary method 825, begins at step 905,
where the analysis computer 100 selects all of the individual
activities associated with a group of jobs with data stored in the
memory storage device or database 705 and then selects the first
individual activity type from the multiple activity types to
analyze. In the exemplary embodiment of FIG. 15, the first activity
type is pulling out of hole tubing (POOH tubing). In step 910, the
analysis computer 100 receives the sensor data or time data for
multiple instances of the selected activity. In one exemplary
embodiment, the times to complete each instance of the activity are
received by the analysis computer 100 from the memory storage
device or database 705. The sensor data or time data received is
sorted from lowest value to highest value in step 915. For example,
when the data received is the completion time for each instance of
the activity of POOH tubing, the analysis computer 100 sorts the
group of completion times for the POOH tubing from lowest to
highest. In an alternative embodiment, the completion times or
other sensor data are sorted from highest to lowest, sorted in
another manner, or not sorted at all.
[0053] In step 920, the median data point from the received, sorted
data is determined. In one exemplary embodiment, the analysis
computer 100 calculates the median data point. FIG. 16 provides one
exemplary method for how the analysis computer 100 calculates the
median data point for the received, sorted data. The median value
for the received, sorted data is determined in step 925. In one
example, the analysis computer 100 calculates the median value for
the received, sorted data. FIG. 17 provides one exemplary method
for how the analysis computer 100 calculates the median value,
which in this example is for completion times for POOH tubing.
[0054] In step 930, a determination is made for a lower level
boundary (LLB) for the received sensor or time data. In one
exemplary embodiment, the analysis computer 100 determines the
lower level boundary based on a pre-set, pre-programmed level. In
this exemplary embodiment, the pre-programmed level for the lower
level boundary is the twenty-fifth percentile of received, ordered
data points and is described as a quartile. The upper level
boundary (ULB) for the received sensor or time data is determined
in step 935. In one exemplary embodiment, the analysis computer 100
determines the upper level boundary based on a pre-set,
pre-programmed level. In this exemplary embodiment, the
pre-programmed level for the upper level boundary is the
seventy-fifth percentile of received, ordered data points and is
also described as a quartile. Thus, in the example above, only the
fifty percent of data points closest to the median data point will
be used for calculating the natural process limits and the moving
range. FIG. 16 presents exemplary calculations for determining the
lower level boundary and the upper level boundary based on the
number of received and sorted data points in the 2.sup.nd and
3.sup.rd row. While the exemplary embodiment sets the lower level
boundary at the twenty-fifth percentile, in alternative
embodiments, the lower level boundary can be anywhere in a range
between 1 and 49 percent. Further, while the exemplary embodiment
sets the upper level boundary at the seventy-fifth percentile, in
alternative embodiments the upper level boundary can be anywhere in
a range between 51 and 99 percent.
[0055] Once the upper and lower level boundaries have been
calculated for the particular activity, the analysis computer 100
reviews each of the data points to determine if they are between
the upper and lower level boundaries. If the data is between the
boundaries, the "data point between boundary" branch is followed to
step 830. Otherwise, the "outside of boundary" branch is followed
to step 945. The data points that are determined to be between the
upper and lower level boundaries are sometimes referred to as the
"center-cut data".
[0056] In step 945, the inner quartile (IQ) is calculated. In one
exemplary embodiment, the analysis computer calculates the inner
quartile. Further, in one exemplary embodiment, the equation for
determining the inner quartile is the value of the upper level
boundary minus the value of the lower level boundary or ULB-LLB=IQ.
The upper gross error boundary is determined in step 950. In one
exemplary embodiment, the upper gross error boundary is determined
by the analysis computer 100. In this exemplary embodiment, the
upper gross error boundary is calculated as the product of the
inner quartile and a constant (C), which is then added to the upper
level boundary or ULB+(C*IQ). In one exemplary embodiment, the
constant is a value of 1.5, however, other values ranging from
0.1-10 are within the scope and spirit of this disclosure. In step
955, the lower gross error boundary is determined. In one exemplary
embodiment, the lower gross error boundary is determined by the
analysis computer 100. In this exemplary embodiment, the lower
gross error boundary is calculated as the product of the inner
quartile and a constant (C), which is then subtracted from the
lower level boundary or LLB-(C*IQ). In one exemplary embodiment,
the constant is a value of 1.5, however, other values ranging from
0.1-10 are within the scope and spirit of this disclosure.
[0057] In step 960, the data points that were outside of the
boundary in step 940 are selected and evaluated against the upper
and lower gross error boundaries by the analysis computer 100. In
step 965, an inquiry is conducted to determine if the value of each
particular data point falls within the upper and lower gross error
boundaries. This determination is typically made by the analysis
computer 100. If the data point does not fall within the upper and
lower gross error boundaries, the NO branch is followed to step
970, where additional analysis is conducted with regard to that
particular data to determine if the data value for the instance of
the activity is correct or needs to be adjusted. For example, the
data can be sent to the rig operator or rig supervisor to evaluate
and compare the electronic data against written records or other
information to determine if the electronic data that fell outside
of the boundaries was accurate. The process then continues to step
975. Returning to step 965, if the data value for the instance of
the activity is within the upper and lower gross error boundaries,
the YES branch is followed to step 975.
[0058] In step 975, an inquiry is conducted to determine if there
is data for another instance of the activity. If so, the YES branch
is followed to step 960. On the other hand, if there is not data
for another instance of the activity to be evaluated, the NO branch
is followed to step 905 to select another activity for
evaluation.
[0059] FIG. 10 is a flow chart presenting a method 830 for
conducting a tech limit activity review of sensor, time, or other
activity data in accordance with one exemplary embodiment.
Referring now to FIGS. 1-10 and 16, the exemplary method 830 begins
at step 1005, where the analysis computer 100 sorts the center-cut
data in chronological order. The median data point for the
center-cut data is calculated in step 1010. In one exemplary
embodiment, the calculation of the median data point is completed
by the analysis computer 100. The median data value (M) is
determined from the center-cut data in step 1015 and can be
calculated or determined, for example, by the analysis computer
100. FIG. 16 presents an exemplary calculation of the median data
point and median value for the exemplary center-cut data in the
fourth row.
[0060] In step 1020, the moving range of the center-cut
chronologically ordered data is determined. In one exemplary
embodiment, the analysis computer 100 calculates the moving range
for the center-cut, chronologically ordered data. In one exemplary
embodiment, the moving range is the absolute value of the
difference in two values in, for example, chronological order. Once
the moving range has been calculated for the chronologically
ordered data, the median (MMR) for the moving range is determined
in step 1025. In certain exemplary embodiments, the median (mMR)
for the moving range is calculated or determined by the analysis
computer 100. In step 1030, if necessary, the upper natural process
limit (UPL) is determined. In one exemplary embodiment, the
determination is made by the analysis computer 100 and is
calculated based on the equation UPL=M+(X*mMR), where X is a
constant. In certain exemplary embodiments, the constant X is equal
to t.sub..sigma., which is sometimes referred to in the art as
3-Sigma and in certain exemplary embodiments is equal to 3.145.
Alternatively, the constant (X) can be any number between
0.5-10.
[0061] In step 1032, if necessary, the lower natural process limit
(LPL) is determined. For certain data being evaluated it may only
be compared to the UPL, the LPL, or it may be evaluated to
determine if it is between a UPL and LPL. The analysis computer
100, for example, can be programmed to know which data from which
activities need be compared to which individual or set of natural
process limits. In the example discussed above regarding the data
being completion times for a particular activity, for example, the
analysis computer 100 calculates an upper natural process limit for
completion time for the activity being analyzed based on the
multiple instances of time completion data initially received by
the analysis computer 100 in step 820 of FIG. 8. Row 5 of FIG. 16
presents and example calculation of the 3-Sigma value.
[0062] In step 1034, once the upper natural process limit, the
lower natural process limit, or the upper and lower natural process
limits have been calculated, the analysis computer 100 compares
each value of the sensor data or time data to the upper and/or
lower natural process limits. For example, using the completion
time for each instance of the activity example above, only an upper
natural process limit would be calculated and the completion times
for each instance of the activity would be compared to the upper
natural process limit to determine which completion times were
greater than the upper natural process limit. Alternatively, for
other types of sensor or time data, both upper and lower natural
process limits or just lower natural process limits may be
calculated and the sensor or time data may be compared to both
upper and lower natural process limits or just the lower natural
process limits as a basis for determining which instances include
data that is outside of the natural process limit range.
[0063] An inquiry is conducted in step 1035 to determine if the
data for a particular instance of the selected activity is within
the particular natural process limit (i.e. less than the upper
natural process limit, greater than the lower natural process limit
or between the upper and lower natural process limits). In one
exemplary embodiment, the determination is made by the analysis
computer 100. Using the completion times scenario above as an
example, if the completion time for the instance is greater than
the upper natural process limit value, then it would be outside of
the range and the NO branch is followed to step 1040, where the
analysis computer 100 flags that instance or adds that instance of
the activity to a list of out of range instances of the activity.
The process then continues to step 1045. Returning to step 1035, if
the completion time for the instance is less than or equal to the
upper natural process limit value, then the value is within the
range and the YES branch is followed to step 1045.
[0064] In step 1045, an inquiry is conducted by the analysis
computer 100 to determine if there is another instance of the
activity to compare to the natural process limits. If there is
another instance, the YES branch is followed back to step 1030 to
compare the data value of the next instance to the particular
natural process limit(s). Otherwise, the NO branch is followed to
step 1050. In step 1050, additional analysis is conducted on each
instance of the activity that is not within the natural process
limit range. This additional analysis can be completed by the
analysis computer 100, one or more supervisors over the particular
instance of the activity that was not within the natural process
limit(s), or a combination of both. In certain exemplary
embodiments, the additional analysis can include the supervisor or
other person asking or answering questions to determine why the
instance of the activity exceeded one of the natural process
limits. This can include completing a set of drop down menus
provided by the analysis computer 100 that describe possible
reasons why the instance of the activity was outside of the natural
process limit range. Additionally, a root cause analysis can be
conducted to determine why the data for that particular instance of
the activity was outside of the natural process limit range.
[0065] In step 1055, an inquiry is conducted to determine if there
is another activity on which to conduct analysis. In one exemplary
embodiment, the determination is made by the analysis computer 100
reviewing the data and the types of activity associated with the
data in the database 705. If there is another activity, the YES
branch is followed to step 820 of FIG. 8 to receive the data for
multiple instances of the next activity. Otherwise, the NO branch
is followed to step 835 of FIG. 8. In one exemplary embodiment, the
analysis computer 100 continues to loop through the process until
all of the activities have been analyzed. Based on the data
obtained, the analysis computer 100 generates reports, such as the
job efficiency report of FIG. 18 or the job summary report of FIGS.
19A-C.
[0066] FIG. 11 is a flow chart presenting an exemplary method for
conducting additional analysis of sensor data or time data as
described in step 1050 of FIG. 10. Referring to FIGS. 1-11, the
exemplary method 1050 begins at step 1105 where the analysis
computer 100 determines the supervisor for each instance of the
activity that is determined to be outside of the natural process
limit(s) range. In one exemplary embodiment, the instance in the
database 705 can include additional information such as rig number,
job number, job site location, supervisor or other identifying
information to assist the analysis computer 100 in determining who
the supervisor is for the particular instance that is out of range.
In step 1110, the analysis computer 100 transmits a request to the
supervisor to complete a root cause analysis routine. The root
cause analysis routine can be sent by the analysis computer 100 to
the supervisor with the request or a link can be provided, or the
supervisor can access the root cause analysis routine remotely. The
root cause analysis routine can be stored on the analysis computer
100 or another computer system capable of electronically
communicating with the analysis computer 100.
[0067] A series of questions are provided to the supervisor based
on the particular activity to determine the reason why the
particular instance of the activity was outside of the natural
process limit(s) range in step 1115. In one exemplary embodiment,
the questions are provided by the analysis computer 100 in a set of
drop down menus that describe possible reasons why the instance of
the activity was outside of the natural process limit(s) range.
Responses are accepted from the supervisor in step 1120 at, for
example, the analysis computer 100 or another computer communicably
coupled to the analysis computer 100. The responses are stored for
later evaluation in step 1125. In one exemplary embodiment, the
responses are stored in the database 705 by the analysis computer
100. The process then continues to step 1055 of FIG. 10.
[0068] FIG. 12 is a flow chart presenting an exemplary method for
conducting data mining of sensor data or time data for activities
as described in step 835 of FIG. 8. Referring now to FIGS. 1-8 and
12, the exemplary method 835 begins at step 1205 where the analysis
computer 100 selects or receives data for a single instance of an
activity from the database 705. For the ease of discussion, the
following example will be described in reference to retrieving and
evaluating instances of the time to complete a particular activity.
However, the data mining process could also be used on other sensor
and time data for the well service rig 20. In one exemplary
embodiment, the data is obtained from the database 705. In step
1210, the elapsed time for the selected instance of the activity is
reviewed. In one exemplary embodiment, this review is completed by
the analysis computer 100. The analysis computer 100 designates the
total time shown or elapsed for the selected instance as "Gross
Time" in step 1215.
[0069] In step 1220, the analysis computer 100 evaluates other
sensor data associated with this instance of the activity. In one
exemplary embodiment, the other sensor data includes inputs or
selections made by the operator at the display 610 of the computer
605, which can also be stored in the database 705. An inquiry is
conducted in step 1225 to determine if the operator indicated any
wait time while completing this instance of the activity. In one
exemplary embodiment the indication of wait time can be made by an
operator selecting one of the buttons on the display 610 of the
computer 605. Alternatively, the analysis computer 100 can evaluate
other sensor data, such as engine revolutions per minute (RPMs),
hookload or rig weight from sensors 46, 102 and hydraulic pressure
from sensor 80 to determine if the rig 20 was waiting during a
particular activity. If wait time was indicated, the YES branch is
followed to step 1230, wherein the analysis computer 100 subtracts
the amount of wait time from the Gross Time to determine the "Net
Time" to complete the particular instance of the activity. The
process then continues to step 1235. Returning to step 1225, if no
wait time is indicated or determined, the NO branch is followed to
step 1235, where the analysis computer 100 analyzes sensor data to
determine what portion of the Net Time the rig was operating on the
designated activity. In one exemplary embodiment, the analysis
computer 100 or the computer 605 evaluates block movement over time
and gaps or lack of block movement over time. When the computer 100
or 605 determines that the block is not moving, it can designate
that time that the rig 20 was not completing the activity. In
certain exemplary embodiments, the computer 100 or 605, allows for
a certain amount of no activity time from the block data before
beginning to count that time as time that the rig is not completing
the activity. For example, in one exemplary embodiment, the
computer 100 or 605 waits until the block has not shown activity
for two minutes, before beginning to count the time as time the rig
20 was not completing activity. In alternative embodiments, the
baseline no activity time can be an amount other than two minutes,
such as any amount of time between zero and twenty minutes. Once it
determines that the block has not moved for longer than the
designated amount of time, the computer 100 or 605 begins counting
the subsequent no activity time and when the activity is completed,
subtracts that time from the Net Time. In an alternative
embodiment, instead of counting only the subsequent time, it can go
back to the first moment that no activity was detected from the
block and count that as the beginning of the no activity time which
is then subtracted from the Net Time.
[0070] In step 1240, the analysis computer 100 designates the time
determined that the rig 20 spent operating on the particular
instance of the activity as Work Time. The trip activity
coefficient is calculated in step 1245. In one exemplary
embodiment, the trip activity coefficient is calculated based on
the equation of Work Time divided by Net Time and is calculated by
the analysis computer 100. In step 1250, the values for Gross Time,
Wait Time, Net Time, Work Time and trip activity coefficient for
this instance of the activity are digitally stored for later use.
In one exemplary embodiment, these values are stored in the
database 705 by the analysis computer 100. The analysis computer
100 determines the number of tubing, rods, or casing (referred to
collectively hereinafter and in the claims as "tubing") run into
the hole or pulled out of the hole for this instance of the
activity in step 1255.
[0071] In step 1260, an inquiry is conducted by, for example, the
analysis computer 100 to determine if there is another instance of
the activity in the database 705. If there is another instance, the
YES branch is followed back to step 1205. Otherwise, the NO branch
is followed to step 840 of FIG. 8. Alternatively, the NO branch
could be followed to another inquiry to determine with the analysis
computer 100 if there is another activity in the database 705 for
which data mining can be completed. In that alternative, the YES
branch would also be followed to step 1205 and the NO branch would
be followed to step 840 of FIG. 8.
[0072] FIG. 13 is a flow chart presenting an exemplary method for
determining a number of tubing joints pulled during an instance of
a particular activity, as described in step 1255 of FIG. 12.
Referring now to FIGS. 1-8, 12, and 13, the exemplary method 1255
begins at step 1305, where the analysis computer 1305 receives an
activity signal. In one exemplary embodiment, the activity signal
is received based on the rig operator selecting an activity at the
display 610 which is then communicated and included with the data
sent to the analysis computer 100. In step 1310, the start time of
the tripping activity is received. For example, the start time can
be received at the analysis computer 100 either from the database
705 or in real-time or nearly real time from the rig 20 by way of
the modem 98. Alternatively, the determination of the number of
tubing pulled out of or run into the well is determined at the
computer 605. Similarly, the end time of the tripping activity is
received in step 1315. The hook load, tong pressure, and block
position sensor data is received in step 1320. In certain exemplary
embodiments, the sensor data is received at the analysis computer
100. In step 1325, the tripping activity is classified. In one
exemplary embodiment, the classification of the tripping activity
is made by the rig operator by pressing or selecting one of the
buttons on the display 610. This classification information is then
transmitted to the database 705 or the analysis computer 100. The
analysis computer 100 sets the tubing joint length based on the
classification in step 1330.
[0073] In step 1335, the minimum block position for a single trip
of running a tubing string into or out of the well is received and
in step 1340 the maximum block position for the same trip is
received. In one exemplary embodiment, the block position data is
originates from the block position sensor 38 and the analysis
computer 100 is able to analyzes the block position data to
determine the minimum and maximum positions detected for each trip
into or out of the well. The maximum hookload is determined and
received at the analysis computer 100 in step 1345 and the minimum
hookload for that same trip is determined and received at the
analysis computer 100 in step 1350. In one exemplary embodiment,
the maximum and minimum hookload are based on an evaluation of the
sensor readings from the hydraulic pads 92 and the zero weight
setting on the display 610 that are transmitted and stored in the
database 705 or directly transmitted to the analysis computer 100.
Alternatively, the hookload levels can be provided by other weight
sensing means, such as for example, sensors or strain gauges on the
block or line itself. The maximum tong pressure during the same
trip is determined and received at the analysis computer 100 in
step 1355. In one exemplary embodiment, the tong pressure data is
received from the sensor 80 and the analysis computer 100 is able
to review the series of tong pressure data to determine the maximum
pressure sensed during the single trip.
[0074] In step 1360, an inquiry is conducted to determine the
difference between the maximum hook load received for the trip and
the minimum hookload received for the trip. In one exemplary
embodiment, the difference is determined by the analysis computer
100 and the difference must be greater than or greater than or
equal to a predetermined level or the trip will not be used for the
purposes of counting the number of tubing joints. For example, the
predetermined level can be five hundred pounds or any other amount
between one hundred and ten thousand pounds. The determination of
at least a minimum level of change in hookload during a trip is
used by the analysis computer 100 to verify that one or more tubing
joints was either added or removed from the tubing string during
the particular trip. If the difference in the maximum and minimum
hookload is less than the predetermined level, the NO branch is
followed to step 1335. If the difference in the maximum and minimum
hookload is greater than or greater than or equal to the
predetermined level, then the YES branch is followed to step 1365.
The analysis computer 100 determines the difference and compares
the difference to the predetermined level, which can be preset into
the computer 100 in one exemplary embodiment.
[0075] An inquiry is conducted in step 1365 to determine if the
maximum tong pressure was greater than or greater than or equal to
a predetermined tong pressure level. For example, the predetermined
tong pressure level can be four hundred pounds per square inch
(psi) or any other pressure level between one hundred and nine
hundred psi. The determination of at least a predetermined level of
tong pressure during the trip is used by the analysis computer 100
to verify that that tongs were engaged to make up or break out a
portion of the tubing string thereby adding or removing from the
tubing string at least one tubing joint during the trip. If the
maximum tong pressure is less than the predetermined tong pressure
level, then the NO branch is followed to step 1335. However, if the
maximum tong pressure is greater than or greater than or equal to
the predetermined tong pressure level, then the YES branch is
followed to step 1370. The analysis computer 100 compares the
maximum tong pressure during the trip to the predetermined tong
pressure level, which can be preset into the computer 100 in one
exemplary embodiment.
[0076] In step 1370, the analysis computer 100 estimates the number
of tubing joints based on the difference between the maximum and
minimum block positions for the trip and the joint length. For
example, the analysis computer can divide the difference between
the maximum and minimum block position by the joint length and take
the lowest or nearest integer value as an estimate of the number of
tubing joints. In step 1375, an inquiry is conducted to determine
if there is another tripping cycle in the data for the particular
instance of the tripping activity. If so, the YES branch is
followed to step 1335. Otherwise, the NO branch is followed to step
1380, where the analysis computer 100 sums up the total number of
estimated tubing joints pulled out of or run into the well for all
of the trips during the particular instance of the activity. In
step 1380, the analysis computer 100 stores the number of tubing
joints or stands with the other data for this instance of the
activity. In one exemplary embodiment, the data is stored in the
database 705 or internally on the computer 100. The process then
continues to step 1260 of FIG. 12.
[0077] FIG. 14 is a flow chart presenting a method for verifying
that a tubing anchor catcher was set correctly according to one
exemplary embodiment. Referring now to FIGS. 1-14, the exemplary
method 1400 begins at step 1405, where the analysis computer 100
reviews mined data in the database 705. Based on the evaluation of
the mined data, the analysis computer 100 finds instances of
activities where the activity includes setting the tubing anchor
catcher (TAC) in step 1410 and retrieves and/or evaluates the data
for those instances. In certain exemplary embodiments, the rig
operator selects the set TAC activity at the display 610 and this
information about the activity is stored in the database 705. In
step 1415, the rig weight or hookload data is evaluated. In one
exemplary embodiment, this data is evaluated by the analysis
computer 100.
[0078] An inquiry is conducted in step 1420 to determine if there
is a section of the rig weight or hookload data where the hookload
increases to the string weight and holds at that string weight for
a short period of time. In one exemplary embodiment, the analysis
and determination are made by the analysis computer 100, the string
weight is typically the amount of weight for the particular
activity (such as the amount of weight that is determined when the
tubing string is initially picked up (minus the weight of the rig
if rig weight sensors are being evaluated)) and the short period of
time is anywhere in the range of one second to five minutes. If
there is no such section of data, the NO branch is followed to step
1415. Otherwise, the YES branch is followed to step 1425, where the
analysis computer 100 reviews data in the database 705 from the
block position sensor 38 to determine a first period when the block
is moving up. In the area, that the block position data is moving
up, the analysis computer reviews data from the rig weigh or
hookload sensors 46, 102 to determine if within that first period
the hookload or rig weight increases a nominal amount in step 1430.
In one exemplary embodiment, a nominal increase is about 5,000
pounds. In alternative embodiments, the nominal increase can be
anywhere in the range of 1500-50,000 pounds and will typically be
based on the manufacturer's specified guidelines for the particular
tubing anchor.
[0079] In step 1435, the analysis computer 100 reviews block
position data to determine if a second period exists, after the
first period, where block movement is down and evaluates the
hookload or rig weight data during that second period to determine
if the hookload or rig weight decreases a second nominal amount. In
one exemplary embodiment, a second nominal decrease is about 10,000
pounds. In alternative embodiments, the second nominal decrease can
be anywhere in the range of 1500-50,000 pounds and will typically
be based on the manufacturer's specified guidelines for the
particular tubing anchor. In step 1440, the analysis computer 100
reviews block position data to determine if a third period exists,
after the second period, where block movement is up and evaluates
the hookload or rig weight data during that third period to
determine if the hookload or rig weight increases a third nominal
amount. In one exemplary embodiment, a third nominal increase is
about 15,000 pounds (or 10,000 pounds over string weight). In
alternative embodiments, the third nominal increase can be anywhere
in the range of 1500-80,000 pounds and will typically be based on
the manufacturer's specified guidelines for the particular tubing
anchor.
[0080] In step 1445, the analysis computer 100 reviews block
position data to determine if a fourth period exists, after the
third period, where block movement is down and evaluates the
hookload or rig weight data during that fourth period to determine
if the hookload or rig weight decreases a fourth nominal amount. In
one exemplary embodiment, a fourth nominal decrease is about 20,000
pounds (or 10,000 pounds below string weight). In alternative
embodiments, the fourth nominal decrease can be anywhere in the
range of 1500-80,000 pounds and will typically be based on the
manufacturer's specified guidelines for the particular tubing
anchor. In step 1450, the analysis computer 100 reviews block
position data to determine if a fifth period exists, after the
fourth period, where block movement is up and evaluates the
hookload or rig weight data during that fifth period to determine
if the hookload or rig weight increases a fifth nominal amount. In
one exemplary embodiment, a fifth nominal increase is about 20,000
pounds (or 10,000 pounds above string weight). In alternative
embodiments, the fifth nominal increase can be anywhere in the
range of 1500-80,000 pounds and will typically be based on the
manufacturer's specified guidelines for the particular tubing
anchor.
[0081] In step 1455, the analysis computer 100 reviews block
position data to determine if a sixth period exists, after the
fifth period, where block movement and the hookload or rig weight
data during that fifth period are substantially stable for a
predetermined period of time. In one exemplary embodiment, the
predetermined period of time is three minutes or longer. In
alternative embodiments, the predetermined period of time can be
anywhere in the range of ten seconds to twenty minutes and will
typically be based on the manufacturer's specified guidelines for
the particular tubing anchor. In step 1460, if all of the
determinations in steps 1415-1455 have been verified by the
analysis computer, the computer 100 generates a positive
notification that the TAC was set properly. In one exemplary
embodiment, the notification can take the form of a designation on
a report card by way of individual designation of the instance of
the TAC activity and a notification of passing or success on the
report card or alternatively as an increase in the count of set TAC
instances that were completed properly. Similarly, if one or more
of the determinations in steps 1415-1455 were not verified, the
analysis computer generates a negative notification that the TAC
was not set properly in a manner similar to those described above
when the TAC is set properly.
[0082] In step 1460, an inquiry is conducted by the analysis
computer 100 to determine if there is another instance where the
set TAC activity was being completed in the database 705. If so,
the YES branch is followed to step 1415. Otherwise, the NO branch
is followed to step 840 of FIG. 8.
[0083] Although the invention is described with reference to
preferred embodiments, it should be appreciated by those skilled in
the art that various modifications are well within the scope of the
invention. Therefore, the scope of the invention is to be
determined by reference to the claims that follow. From the
foregoing, it will be appreciated that an embodiment of the present
invention overcomes the limitations of the prior art. Those skilled
in the art will appreciate that the present invention is not
limited to any specifically discussed application and that the
embodiments described herein are illustrative and not restrictive.
From the description of the exemplary embodiments, equivalents of
the elements shown therein will suggest themselves to those or
ordinary skill in the art, and ways of constructing other
embodiments of the present invention will suggest themselves to
practitioners of the art. Therefore, the scope of the present
invention is to be limited only by any claims that follow.
* * * * *