U.S. patent application number 10/771065 was filed with the patent office on 2005-09-15 for system and method for optimizing production in an artificially lifted well.
Invention is credited to Cudmore, Julian R., Haskell, Julian B., White, Thomas M..
Application Number | 20050199391 10/771065 |
Document ID | / |
Family ID | 34919678 |
Filed Date | 2005-09-15 |
United States Patent
Application |
20050199391 |
Kind Code |
A1 |
Cudmore, Julian R. ; et
al. |
September 15, 2005 |
System and method for optimizing production in an artificially
lifted well
Abstract
A system and method is provided for optimizing production from a
well. A plurality of sensors are positioned to sense a variety of
production related parameters in a well having a gas lift system.
The sensed parameters are used in creating measured data that can
be applied against a well model. Discrepancies between the well
model and the measured data are used to determine factors
contributing to sub-optimal well performance.
Inventors: |
Cudmore, Julian R.;
(Inverurie, GB) ; Haskell, Julian B.;
(Peterculter, GB) ; White, Thomas M.; (Spring,
TX) |
Correspondence
Address: |
Schlumberger Technology Corporation
Schlumberger Reservoir Completions
14910 Airline Road
P.O. Box 1590
Rosharon
TX
77583-1590
US
|
Family ID: |
34919678 |
Appl. No.: |
10/771065 |
Filed: |
February 3, 2004 |
Current U.S.
Class: |
166/250.15 ;
166/372; 166/66; 166/68 |
Current CPC
Class: |
E21B 43/122
20130101 |
Class at
Publication: |
166/250.15 ;
166/372; 166/068; 166/066 |
International
Class: |
E21B 043/00 |
Claims
What is claimed is:
1. A method of optimizing production in a well, comprising:
operating a gas lift system in a wellbore; gathering a plurality of
production related parameters; matching a well model with measured
data obtained from the production related parameters to determine
discrepancies; and redesigning the gas lift system based on the
discrepancies.
2. The method as recited in claim 1, wherein gathering comprises
measuring the gas injection rate.
3. The method as recited in claim 1, wherein gathering comprises
measuring the fluid production rate.
4. The method recited in claim 1, wherein gathering comprises
obtaining a flowing gradient survey.
5. The method as recited in claim 1, wherein gathering comprises
obtaining temperature data.
6. The method as recited in claim 1, wherein gathering comprises
obtaining temperature data.
7. The method as recited in claim 6, wherein the temperature data
is obtained via a distributed temperature sensing system.
8. The method as recited in claim 1, wherein gathering comprises
obtaining surface parameter measurements.
9. The method recited in claim 1, wherein gathering comprises
obtaining downhole parameter measurements.
10. The method as recited in claim 1, wherein gathering comprises
obtaining episodic measurements.
11. The method as recited in claim 1, wherein gathering comprises
measuring a tubing pressure.
12. The method as recited in claim 1, wherein gathering comprises
measuring a tubing temperature.
13. The method as recited in claim 1, wherein gathering comprises
measuring an injection pressure.
14. The method as recited in claim 1, wherein gathering comprises
measuring an injection temperature.
15. The method as recited in claim 1, wherein gathering comprises
utilizing a multiphase flow meter.
16. The method as recited in claim 1, wherein gathering comprises
measuring a tubing pressure below a gas lift orifice.
17. The method as recited in claim 1, wherein gathering comprises
measuring a casing pressure below a gas lift orifice.
18. The method as recited in claim 1, wherein gathering comprises
measuring temperature via a slickline deployed distributed
temperature sensing system.
19. The method recited in claim 1, further comprising initially
selecting a candidate well by obtaining well test data.
20. The method as recited in claim 1, further comprising initially
selecting a candidate well by obtaining gas lift monitoring
data.
21. The method as recited in claim 1, further comprising initially
selecting a candidate well by obtaining well history data.
22. The method as recited in claim 1, further comprising initially
selecting a candidate well by obtaining completion specific
data.
23. The method as recited in claim 1, further comprising validating
any improvements in production following redesign of the gas lift
system.
24. The method as recited in claim 1, wherein matching comprises
analyzing inflow factors.
25. The method as recited in claim 1, wherein matching comprises
analyzing outflow factors.
26. The method as recited in claim 1, wherein matching comprises
analyzing surface factors.
27. The method as recited in claim 1, wherein redesigning comprises
adjusting a temperature setting.
28. The method as recited in claim 1, wherein redesigning comprises
adjusting a gas injection rate.
29. The method as recited in claim 1, wherein redesigning comprises
changing a component of the gas lift system.
30. The method as recited in claim 1, wherein redesigning comprises
correcting an inlet related limitation.
31. The method as recited in claim 1, wherein redesigning comprises
correcting an outlet related limitation.
32. The method as recited in claim 1, wherein redesigning comprises
correcting a downhole related limitation.
33. A system for optimizing production in a well, comprising: a gas
lift system positioned in the well; a sensor system to sense a
plurality of well related parameters; and a well modeling module
able to automatically compare a calculated model of the well to
measured data based on the plurality of well related parameters to
determine factors detrimentally affecting optimization of
production from the well.
34. The system as recited in claim 33, wherein the sensor system
monitors data in real-time.
35. The system as recited in claim 33, wherein the sensor system
comprises a remote processor system.
36. The system as recited in claim 33, wherein the sensor system is
configured to sense a quantity of injected gas.
37. The system as recited in claim 33, wherein the sensor system
comprises a tubing pressure sensor and tubing temperature
sensor.
38. The system as recited in claim 33, wherein the sensor system
comprises an injection pressure sensor and an injection temperature
sensor.
39. The system as recited in claim 33, further comprising a
multiphase flow data sensor.
40. The system as recited in claim 33, further comprising an
episodic sensor system.
41. The system as recited in claim 40, wherein the episodic sensor
system is configured to obtain a flowing gradient survey.
42. The system as recited in claim 40, wherein the episodic sensor
system is configured to obtain a distributed temperature
profile.
43. A method of optimizing production from a gas lift system
disposed in a well, comprising: flowing a gas through the gas lift
system; obtaining measured data from a plurality of sensors
positioned to sense production related parameters; graphically
plotting a gradient based on the measured data; graphically
plotting a model gradient; and comparing the gradient and the model
gradient to determine whether production can be optimized.
44. The method as recited in claim 43, further comprising
optimizing production performance of the gas lift system.
45. The method as recited in claim 44, further comprising adjusting
the gas lift system to optimize performance.
46. The method as recited in claim 45, wherein adjusting comprises
correcting an inlet related limitation on production.
47. The method as recited in claim 45, wherein adjusting comprises
correcting an outlet related limitation on production.
48. The method as recited in claim 45, wherein adjusting comprises
correcting a downhole related limitation on production.
49. The method as recited in claim 45, wherein adjusting comprises
adjusting a temperature setting.
50. The method as recited in claim 45, wherein adjusting comprises
adjusting a gas injection rate.
51. The method as recited in claim 45, wherein adjusting comprises
changing a component of the gas lift system.
52. The method as recited in claim 45, wherein adjusting comprises
adjusting a choke size.
53. The method as recited in claim 45, wherein adjusting comprises
adjusting a casing pressure.
54. The method as recited in claim 45, wherein adjusting comprises
adjusting a separator operating pressure.
55. The method as recited in claim 45, wherein adjusting comprises
removing a valve restriction.
56. The method as recited in claim 45, wherein adjusting comprises
fixing a tubing hole.
57. The method as recited in claim 45, wherein adjusting comprises
changing a valve spacing.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Field of the Invention
[0002] The present invention relates to artificially lifted oil and
gas wells, and in particular to such wells employing gas lift
technology.
[0003] 2. Description of Related Art
[0004] In many artificially lifted wells, there is potential for
significantly improved operation and increased production. There
are a variety of mechanisms for artificially lifting fluid from a
reservoir, such as gas lift systems. In artificial lift systems, a
variety of mechanical and systemic components can limit
optimization of system usage. For example, gas injection rates may
not be optimal and/or artificial lift system components may be
blocked, damaged, sized improperly, operated at less than optimal
rates, or otherwise present limitations on gaining optimal use of
the overall system.
[0005] Attempts have been made to detect certain specific problems.
However, comprehensive analysis of the well and/or system
components has proved to be difficult once the system is moved
downhole and placed into operation.
BRIEF SUMMARY OF THE INVENTION
[0006] In general, the present invention provides a system and
method of optimizing production in a well having a gas lift system.
The gas lift system is located and operated within a wellbore.
Simultaneously, a plurality of production parameters are monitored
and used to obtain certain desired, measured data indicative of
well operational factors. The measured data are evaluated according
to an optimization model to determine if production is optimized.
If not, the gas lift mechanism is redesigned based on evaluation of
the various production parameters and measured data.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] Certain embodiments of the invention will hereafter be
described with reference to the accompanying drawings, wherein like
reference numerals denote like elements, and:
[0008] FIG. 1 is a schematic illustration of a methodology for
optimizing production in a well, according to an embodiment of the
present invention;
[0009] FIG. 2 is an elevational view of a gas lift system utilized
in a well to lift fluids to a surface location, according to an
embodiment of the present invention;
[0010] FIG. 3 is a flowchart representing a method of selecting and
optimizing production in a well, according to an embodiment of the
present invention;
[0011] FIG. 4 is a diagramatic illustration of an embodiment of a
control system that can be used to automatically carry out the
methodology or portions of the methodology illustrated in FIG.
3;
[0012] FIG. 5 is an illustration of parameters utilized in
candidate selection;
[0013] FIG. 6 is an illustration of a system that can be used to
acquire data for use by the well optimization methodology
illustrated in FIG. 3;
[0014] FIG. 7 is an illustration of an embodiment of a well
performance model;
[0015] FIG. 8 is a graph representing a comparison of measured data
to calculated data;
[0016] FIG. 9 is a graph similar to that of FIG. 8 but following
redesign of the artificial lift system;
[0017] FIG. 10 is a graphical representation of factors that can
affect gas lift redesign;
[0018] FIG. 11 is a graphical representation of correlation
examples that can be used to facilitate gas lift redesign;
[0019] FIG. 12 is a graphical representation of potential
corrective actions that can be taken to optimize production from
the well illustrated in FIG. 2;
[0020] FIG. 13 is a flowchart illustrating a selected methodology
of the present invention for optimizing gas injection rate;
[0021] FIG. 14 is a flowchart illustrating a portion of the
methodology of FIG. 13 when the well flows and takes gas;
[0022] FIG. 15 is a flowchart illustrating a portion of the
methodology of FIG. 13 when the well flows and does not take gas;
and
[0023] FIG. 16 is a flowchart illustrating a portion of the
methodology of FIG. 13 when the well flows and the gas injection is
irregular.
DETAILED DESCRIPTION OF THE INVENTION
[0024] In the following description, numerous details are set forth
to provide an understanding of the present invention. However, it
will be understood by those of ordinary skill in the art that the
present invention may be practiced without these details and that
numerous variations or modifications from the described embodiments
may be possible.
[0025] The present invention generally relates to a system and
method for optimizing production from a well in which fluids are
lifted by a gas lift system deployed in the well. The process
allows the artificial lift system to be analyzed and diagnosed to
facilitate system redesign that optimizes performance with respect
to the productivity of the well.
[0026] A general approach to optimization is set forth in the
flowchart of FIG. 1. Initially, underperforming, artificially
lifted wells are identified, as set forth in block 20. Upon
determining the underperforming wells, the cause of the
underperformance is identified, as illustrated by block 22.
Identification of the cause of the underperformance enables the
implementation of corrective procedures, e.g. gas lift redesign, as
illustrated in block 24. Effectively, a cause or problem is
identified and an effect or correction is undertaken to optimize
performance. Depending on the environment and the specific
equipment used, the causes and the selected effects, i.e.,
corrective actions, may vary as discussed more fully below.
[0027] Although this general approach can be applied to a variety
of artificially lifted wells, the present description will
primarily be related to the optimization of a well in which a gas
lift system is used to artificially lift the well fluid. In FIG. 2,
an embodiment of a gas lift system 26 is illustrated. In this
embodiment, gas lift system 26 is used to produce fluid from a
wellbore 28 drilled or otherwise formed in a geological formation
30. A wellbore section of the gas lift system 26 is suspended below
a wellhead 32 disposed, for example, at a surface 34 of the earth.
A tubing 36 provides a flow path within wellbore 28 through which
well fluid is produced to wellhead 32.
[0028] As illustrated, wellbore 28 is lined with a wellbore casing
38 having perforations 40 through which fluid flows from formation
30 into wellbore 28. For example, a hydrocarbon-based fluid may
flow from formation 30 through perforations 40 and into wellbore 28
adjacent an intake 42 of tubing 36. Upon entering wellbore 28, the
well fluid is produced upwardly by gas lift system 26 through
tubing 36 to wellhead 32. From wellhead 32, the produced well fluid
is directed through control valve 44 to a separator 46 where gas
and liquid are separated. The substantially liquid portion of well
fluid is directed to a desired location, such as stock tank 48.
[0029] Although gas lift system 26 may comprise a wide variety of
components, the example in FIG. 2 is illustrated as having a gas
compressor 50 that receives an injection gas from a gas source,
such as separator 46. Gas compressor 50 forces the gas through a
flow control valve 52, through wellhead 32 and into the annulus
between tubing 36 and casing 38. A packer 54 is designed to seal
the annulus around tubing 36. (In the embodiment illustrated,
packer 54 is disposed proximate intake 42.) The pressurized gas
flows through the annulus and is forced into the interior of tubing
36 through one or more gas lift valves 56 disposed in corresponding
side pocket mandrels 58. The gas flowing through gas lift valves 56
draws well fluid into intake 42 and upwardly through the interior
of tubing 36. The mixture of injected gas and well fluid move
upwardly through control valve 44 and are separated at separator 46
which directs the well fluid to stock tank 48 and the injection gas
back to gas compressor 50.
[0030] One example of a methodology that can be used in optimizing
production in a gas lifted well can be described with reference to
the illustrated flowchart of FIG. 3. Initially, the candidate wells
are selected based on an indication of underperformance (block 60).
In the selected well or wells, a preliminary analysis (block 62) is
made to verify the candidate well is not producing at an optimal
level and is suitable for production optimization. Subsequently,
data is acquired that will help gauge the performance of the gas
lift system 26 (block 64). The data is based on a variety of
production related parameters that may be sensed or otherwise
obtained. In many applications, the sensing of production related
parameters in real-time substantially improves the accuracy and
comprehensiveness of the "operational picture" used in analyzing
potential problems that contribute to underperformance. Once the
data is acquired, the well is modeled based on known parameters
related to the well and the specific gas lift system. The modeled
well can then be matched to measured data, e.g. data based on the
sensed production parameters, as illustrated in block 66. If the
well is operating at a sub-optimal level, a gas lift redesign is
implemented and validated (block 68). It should be noted that
although the gas lift system is a major factor in the outflow
performance of a well, the lift system is codependent with other
factors, such as reservoir inflow and surface system performance.
Thus, the optimization methodology benefits from an understanding
of well performance, including inflow, outflow and surface
performance, in determining the cause of sub-optimal
performance.
[0031] Some or all of the methodology outlined with reference to
FIG. 3 is automated via a processing system 70, as diagramatically
illustrated in FIG. 4. Processing system 70 may be a computer-based
system having a central processing unit (CPU) 72. CPU 72 is
operatively coupled to a memory 74, as well as an input device 76
and an output device 78. Input device 76 may comprise a variety of
devices, such as a keyboard, mouse, voice-recognition unit,
touchscreen, other input devices, or combinations of devices.
Output device 78 may comprise a visual and/or audio output device,
such as a monitor having a graphical user interface. Additionally,
the processing may be done on a single device or multiple devices
located at the well, away from the well, or with some devices
located at the well and other devices located remotely.
[0032] Processing system 70 can be used to input parameters
regarding candidate selection. The system also can be used to
receive data during the data acquisition phase, to model the well
by comparing calculated or modeled values to measured data, and to
facilitate gas lift redesign based on the measured data. However,
it should be recognized that the design and implementation of
processing system 70 can vary substantially from one application to
another, and the desired interaction between processing system 70
and an optimization technician may vary based on design
considerations and application constraints.
[0033] As briefly described with reference to FIG. 3, candidate
wells are initially selected. In, for example, oilfields with high
populations of gas lift systems, it is important that likely
candidates for optimization are filtered from wells that are
already running at optimum conditions and at optimum rates. In one
approach, candidate selection may be used to filter out wells
according to priority of potential oil production gain, thereby
helping attain maximum success in a minimum timeframe. The
recognition of sub-optimally lifted wells relative to other wells
in the field is not a straightforward task and requires evaluation
of various data and information.
[0034] The ability to determine likely candidates for optimization
often relies on obtaining accurate data related to the subject
wells. For example, it can be useful to monitor a data trend to
determine the consistency and accuracy of the data relied on in
determining likely candidates for optimization.
[0035] Also, it can be important to initially examine a variety of
factors before selecting candidates for optimization. In FIG. 5,
four candidate selection factors are illustrated, specifically,
well test data 80, available gas lift monitoring data 82,
completion data 84, and well history 86.
[0036] When interpreting existing well test data, it is beneficial
to understand the accuracy level of the data and how it was
acquired. Therefore, before selecting candidates it is helpful to
examine any raw data related to production. For example, a
differential pressure chart indicates the gas injection rate
behavior, and a water cut reading of samples can indicate stability
of the water cut. If the historical data is not consistent or
cannot be logically analyzed, it may be necessary to test the well
to establish "baseline" production values. After preliminary
screening, the most prominent optimization candidates can be
selected.
[0037] Available gas lift monitoring data also can affect candidate
selection. During historical operation of a gas lift, certain
parameters may be measured and values recorded on a periodic basis.
Any of this monitoring data, e.g. gas injection rate, gas injection
line pressure, casing head pressure, wellhead pressure, and
wellhead temperature, can be helpful in assessing the potential for
production optimization.
[0038] Completion data also is a factor that can affect the
potential for production optimization. A review of a completion
design diagram provides valuable information as to the gas lift
configuration and specific downhole equipment used in the system.
Such information may include depth and type of mandrels, type of
gas lift valves, and port sizes. The configuration and equipment
can help provide a better understanding of well behavior.
[0039] Well history data can also provide information that will aid
in candidate selection. Well history data can include flowing
gradient surveys, well intervention and stimulation information,
records of chemical treatment, and other information that can help
provide a basic understanding of the well. All of these factors can
be used to reduce the subjectivity of the candidate selection
process.
[0040] Upon selecting a candidate well, data is acquired to gauge
the performance of the gas lift system. Typically, data is acquired
by a variety of sensors that may comprise, for example, distributed
temperature sensors and pressure sensors. Also, it can be
beneficial to utilize sensor systems able to provide real-time
streaming data. Trended data with common time and date facilitates
the selection of points of interest from trend lines to provide
more accurate "snap shots" of well operation to aid in
analysis.
[0041] In FIG. 6, an embodiment of a sensor system used to
facilitate optimization of a gas lift system is illustrated. The
various sensors may be coupled to processing system 70 which is
able to assimilate the data and display relevant information to a
technician and/or utilize the data in performing analyses on the
well. Although a variety of parameters may be sensed to provide
measured data that can be used in analysis of a given well, FIG. 6
illustrates examples of sensors and sensed parameters that may be
helpful to the analysis. The sensed parameters are divided into
three example groups, including surface measurements 88, downhole
measurements 90, and episodic measurements 92. Many of the sensed
parameters can be obtained in real-time and delivered to processing
system 70 for analysis. Processing system 70 can be located locally
at the well or remotely. If located remotely, signals from the
sensors can be transmitted to processing system 70 by hardwire or
wirelessly, e.g. via satellite communication. Additionally,
processing system 70 may comprise a single unit or multiple linked
units.
[0042] Examples of surface sensors and/or sensed parameters include
tubing pressure and temperature sensors 94, injection pressure and
temperature sensors 96, injection sensors 98 for sensing the gas
injection rate, and multiphase flow sensors 100. Examples of
downhole sensors and/or sensed parameters include tubing pressure
sensors 102 disposed below the orifice, casing pressure sensors 104
disposed below the orifice, and distributed temperature sensors
106. Examples of episodic sensors include sensors 108 for
determining a flowing gradient survey and a deployable distributed
temperature sensing (DTS) system 110 that may be deployed, for
example, by a slickline. In other applications, it may be desirable
to utilize additional sensors, other sensors, or smaller groups of
sensors than those illustrated. For example, in some applications,
the methodology discussed herein may be carried out with a unique
subset of the illustrated sensors, such as sensors 94, 96, 98, 100,
108, and 110. Additionally, commercially available systems may be
suitable to determine at least some of the measured data. An
example of a commercially available system is the PhaseTester
portable multiphase well testing system available from Schlumberger
Technology Corporation of Sugar Land, Tex., USA.
[0043] In addition to acquiring data, the subject well and the gas
lift system is modeled. However, modeling of the well will vary
depending on the environment in which the wellbore is drilled,
formation parameters, and type and componentry of the gas lift
system. Proper modeling of the well enables comparison of
calculated values (model values) to measured data based on the
various production related parameters sensed or otherwise obtained.
As illustrated in FIG. 7, a well performance modeling program 112
can be utilized on processor system 70 to match calculated or model
values to the corresponding measured data 114 based on actual
production related parameters, such as those described above with
reference to FIG. 6.
[0044] A main philosophy in well modeling is the matching of a
model well, e.g. optimized well, to measured data from the actual
well to determine areas of sub-optimal performance. However, the
more invalidated or unknown parameters used in the model, the
greater the uncertainty and the greater the number of assumptions
that must be used in the modeling. This, of course, increases the
difficulty in matching the model with actual data in any meaningful
way. Furthermore, the model and specific calculated data used to
prepare a model for comparison to measured data can vary
substantially depending on the well, wellbore environment, type of
artificial lift equipment, and variety of lift system components.
In preparing a well model, it can be helpful to utilize a modeling
program on processing system 70. One example that can be used in
modeling gas lift systems is a software tool known as PIPESIM which
provides steady-state, multiphase flow simulation for oil and gas
production systems and is also available from Schlumberger
Technology Corporation.
[0045] As briefly discussed above, real-time collection of data
from a wide variety of sensors and the use of that data in
assimilating measured data for comparison to a predetermined model
lays important groundwork for optimization of a given well.
Potentially, the performance modeling program 112 can be used to
model a variety of well-related performance characteristics.
Typically, the program will prompt a user, via output device 78,
for well related parameters that can be used to model one or more
aspects of the subject well. The performance modeling program 112
also receives actual data from, for example, sensors such as those
illustrated and described with respect to FIG. 6. The contrast
between the model characteristics and the actual measured data can
be presented to a technician through output device 78. For example,
the comparison can be presented graphically, as illustrated in FIG.
8.
[0046] In the example illustrated in FIG. 8, the calculated
variable is inlet pressure. The modeling program utilizes the
wellhead pressure obtained from a flowing gradient survey and the
liquid rate that can also be obtained from the flowing gradient
survey. Vertical flow correlations to be checked against the
flowing gradient survey are selected using engineering judgment. A
gradient 116 is calculated by the performance modeling program 112
and graphically displayed via output device 78, as illustrated. In
this example, gradient 116 is illustrated in graphical form on a
graph 118 that plots "pressure" along the x-axis against
"elevation" along the y-axis.
[0047] The specific gradient 116 can be determined based on a
variety of known correlations. For example, a correlation known as
the Hagedorn and Brown (HBR) correlation is used to provide the
illustrated gradient 116. A second gradient 120, based on measured
data, also is plotted on graph 118. Thus, the modeled or calculated
gradient can be compared to the actual measured data. In this
example, a substantial pressure difference is illustrated between
the calculated pressure and the measured pressure, particularly at
greater depths. As a result, corrective action can be taken and the
measured data re-plotted against the model gradient, as illustrated
in FIG. 9. Although the appropriate corrective action can vary
substantially from one well/application to another, the
optimization illustrated in FIG. 9 resulted from increasing the
"hold-up" factor which essentially increased the weight of the
hydrostatic column.
[0048] As described above, well optimization sometimes can result
from simple adjustments to the gas lift system design. However,
other modeling results can indicate more substantial redesigns. In
either situation, a thorough understanding of the well and the
conditions in the well over time can greatly improve the gas lift
redesigns. As illustrated in FIG. 10, gas lift redesigns can
benefit from a variety of factors, such as selecting the best
correlations for use in modeling (block 122), obtaining accurate
information related to the completion (block 124) and the reservoir
(block 126). Other factors can include knowledge of fluid
properties (block 128) and surface parameters (block 130).
[0049] Examples of completion related information that can be
useful in gas lift design include type of completion, tubing size,
casing size, and any deviations of the well. Well deviation, for
example, can affect the inflow and outflow performance of the well
and the type of gas lift mandrel suitable for optimum production
from such wells. Useful reservoir information may include the type
of producing sand, the static bottomhole pressure or reservoir
pressure, the static bottomhole temperature, permeability, sand
thickness, skin and water leg. Examples of useful fluid properties
include viscosity, bubble point pressure, gas-oil-ratio, API
gravity data, gas specific gravity, and water salinity. Useful
surface information may include separator pressure, flow line
considerations, and compressor pressure. Many of these gas lift and
environmental factors also can influence the design of modeling
programs for modeling a given well or wells.
[0050] Along those same lines, the effectiveness of the modeling
also greatly influences gas lift redesign and the ability to
optimize performance in a given well. It is not only the quality of
the data input in a given modeling program but also the
correlations used in the model. Some correlations between
calculated values and measured data can be more important than
others. For example, in redesigning gas lift systems, examples of
correlations that can play an important role are illustrated in
FIG. 11 and include bubble point pressure correlations 132, oil
viscosity correlations 134, and multiphase flow correlations 136.
The redesign may involve a simple setting readjustment, such as
adjusting a temperature setting or adjusting the gas injection
rate. However, the redesign also may involve more substantial
changes to the gas lift system, such as changing components of the
gas lift system.
[0051] As illustrated in FIG. 12, various corrective actions 138
can be taken to optimize production from the subject well based on
indications of problem areas from the well modeling. With gas lift
systems, the corrective action typically is related to inlet
options 140, outlet options 142, and downhole options 144.
Determination of potential corrective actions can be performed
automatically by processing system 70, or processing system 70 can
be designed to output an indication of deviation between modeled
values and measured data, e.g. FIG. 8, for review by a
technician.
[0052] By way of example, high casing pressure or excessive gas
usage relative to model values may indicate an inlet problem, such
as a choke sized too large. A showing of excessive gas usage can,
for example, be indicative of an inlet problem, such as high casing
pressure. Other deviations from model parameters can indicate
outlet problems, such as valve restrictions, high-back pressure,
and improper separator operating pressure. Other deviations can
indicate downhole problems, such as a hole in the tubing, a well
blowing dry gas, a well that will not take any input gas, valve
spacing that is too wide, and other downhole problems. A wide
variety of such problems can be corrected to optimize production
from the well.
[0053] After taking a corrective action or actions, the results may
be validated, as illustrated by block 146 in FIG. 12. This
assessment can be an important part of the redesign, because it
serves to check whether production from a given well has been
improved and, if so, whether the well production has been fully
optimized. In the final optimization, as illustrated by block 148,
the well is operated, and measured data is again compared to the
well model to determine the existence of any remaining
discrepancies indicating sub-optimal performance. Final well
optimization can also involve reviewing data from an entire
production network to determine whether changes to a single well
has affected the performance of the overall production network.
[0054] By way of example, FIGS. 13-16 illustrate one selected
methodology of the present invention for optimizing gas injection
rate. Referring to FIG. 13, following identification of an
underperforming well, a flowing survey of the well is taken (block
1302). The continuous flow design diagnostics of the present
invention, described above, are then applied (block 1304). As
illustrated, the well does (block 1306) or does not (block 1308)
flow.
[0055] Assuming, for example, that the well flows, it will take gas
(block 1310), not take gas (block 1312), or take gas irregularly
(block 1314). FIG. 14 illustrates the methodology when the well
flows and takes gas (block 1402). Under these circumstances,
injection will either be through a gas lift valve (block 1404) or
not (block 1406). If injection is through a gas lift valve which is
the deepest valve (block 1408), a reevaluation of the system must
be made (block 1410) to determine whether or not the gas injection
rate is optimized (block 1412).
[0056] If the injection is not through the deepest gas lift valve
(block 1408), an evaluation must be made for a deeper point (block
1414) before checking for mechanical problems (block 1416). If no
mechanical problems are found, the system is redesigned for deeper
injection (block 1418) before reevaluation (block 1410). If
mechanical problems are found, the restriction must be removed
(block 1420) and workover must be considered (block 1422) before
reevaluation (block 1410).
[0057] If injection is not through a gas lift valve (block 1406),
there may either be a hole in the tubing (block 1424) or a leak in
the sidepocket mandrel (block 1426). In case of a hole in the
tubing, a packoff is installed (block 1428) before the system is
reevaluated (block 1410). In case of a sidepocket mandrel leak, the
gas valve is reinstalled (block 1430) before installation of a
packoff (block 1432) and reevaluation of the system (block
1410).
[0058] FIG. 15 illustrates the methodology when the well flows but
does not take gas (block 1502). Under these circumstances, there
may be a failed gas lift valve (block 1504), a casing bridge (block
1506), and excessively high gas lift valve setting (block 1508), an
excessively low gas lift valve design temperature (block 1510), or
a surface gas input problem (block 1512). The remedial actions are,
respectively, to change the gas lift valve (block 1514), to pump
chemical (block 1516) followed by water (block 1517), redesign the
gas lift valve for a lower pressure (block 1518), redesign the gas
lift valve for a higher temperature (block 1520), or check for a
plugged or frozen choke (block 1522). In each case, following the
specified remedial action the system is reevaluated (block 1524) to
ascertain that the gas injection rate is optimized (block
1526).
[0059] FIG. 16 illustrates the methodology when the well flows, but
gas injection is irregular (block 1602). Under these circumstances
the problem will be either a subsurface problem (block 1604) or a
surface problem (block 1606). A subsurface problem will manifest
itself in either low (block 1608) or high (block 1610) casing
pressure. When a low casing pressure is evident, there may be a
hole in the tubing (block 1612), the unloading valve may have lost
pressure (block 1614), the valve port fluid may be cut (block
1616), or the sidepocket mandrel may be leaking (block 1618). Once
the cause of the low casing pressure is ascertained and remedied,
the system is reevaluated (block 1620) to determine if the gas
injection rate optimized (block 1622).
[0060] When a high casing pressure is evident, the unloading valve
may have gained pressure (block 1624), the gas lift valve may be
operating too deep (block 1626), or the valve port size may be too
small (block 1628). Upon diagnosing the cause of the high casing
pressure and correcting the problem, the system is reevaluated
(block 1620) to determine if the gas injection rate is optimized
(block 1622).
[0061] A surface problem (block 1606) may be reflected in, for
example, an unstable gas supply (block 1630) or an unstable back
pressure (block 1632). Unstable gas supply pressure may be due to
an unstable compressor discharge (block 1634), in which case a
redesign for higher (block 1636) should be undertaken before
reevaluation (block 1620) and optimization of the gas injection
rate (block 1622).
[0062] Finally, unstable back pressure (block 1632) may be due, for
example, to an adjacent well heading in a shared manifold (block
1638) or an unstable separator back pressure (block 1640) which
should be corrected before reevaluation (block 1620) and
optimization of gas injection rate (block 1622).
[0063] Although, only a few embodiments of the present invention
have been described in detail above, those of ordinary skill in the
art will readily appreciate that many modifications are possible
without materially departing from the teachings of this invention.
Accordingly, such modifications are intended to be included within
the scope of this invention as defined in the claims.
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