U.S. patent application number 16/523837 was filed with the patent office on 2020-02-06 for drilling performance optimization with extremum seeking.
This patent application is currently assigned to HALLIBURTON ENERGY SERVICES, INC.. The applicant listed for this patent is HALLIBURTON ENERGY SERVICES, INC.. Invention is credited to Robert P. DARBE, Nazli DEMIRER, Julien MARCK, Umut ZALLUHOGLU.
Application Number | 20200040720 16/523837 |
Document ID | / |
Family ID | 69228387 |
Filed Date | 2020-02-06 |
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United States Patent
Application |
20200040720 |
Kind Code |
A1 |
ZALLUHOGLU; Umut ; et
al. |
February 6, 2020 |
DRILLING PERFORMANCE OPTIMIZATION WITH EXTREMUM SEEKING
Abstract
A drilling optimization method including perturbing one or more
drilling control parameters with a periodic or a stochastic signal
during a drilling process, estimating at least one drilling
performance measure to optimize the drilling process based on the
perturbed one or more drilling control parameters, perturbing the
at least one drilling performance measure with a periodic or a
stochastic perturbation source through demodulation, determine a
next best estimate of the one or more drilling control parameters
to optimize the at least one drilling performance measure,
perturbing the next best estimate by a periodic or a stochastic
perturbation source through modulation, and feeding the
perturbation next best estimates of the one or more drilling
control parameters back to the drilling process.
Inventors: |
ZALLUHOGLU; Umut; (Humble,
TX) ; MARCK; Julien; (Houston, TX) ; DARBE;
Robert P.; (Tomball, TX) ; DEMIRER; Nazli;
(Houston, TX) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
HALLIBURTON ENERGY SERVICES, INC. |
Houston |
TX |
US |
|
|
Assignee: |
HALLIBURTON ENERGY SERVICES,
INC.
Houston
TX
|
Family ID: |
69228387 |
Appl. No.: |
16/523837 |
Filed: |
July 26, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62713009 |
Aug 1, 2018 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
E21B 44/02 20130101;
E21B 7/04 20130101; E21B 44/00 20130101 |
International
Class: |
E21B 44/00 20060101
E21B044/00 |
Claims
1. A method comprising: perturbing a drilling control parameter
with a periodic or a stochastic signal during a drilling process;
estimating or calculating a drilling performance measure to
optimize the drilling process based on the perturbation of the
drilling control parameter; perturbing the drilling performance
measure by multiplying the drilling performance measure with a
periodic or a stochastic perturbation source through demodulation;
determining a next best estimate of the drilling control parameter
to optimize the drilling performance measure; perturbing the next
best estimate by a periodic or a stochastic perturbation source
through modulation; and feeding the perturbed next best estimate of
the drilling control parameters to the drilling process.
2. The method of claim 1, further comprising feeding the drilling
performance measure through a high-pass filter.
3. The method of claim 1, further comprising feeding the perturbed
drilling performance measure through a low-pass filter.
4. The method of claim 1, wherein determining the next best
estimate comprises integrating a gradient to calculate the next
best estimate.
5. The method of claim 1, wherein feeding next best estimate to the
drilling process includes adjusting the one or more drilling
control parameters thus optimizing the selected at least one
drilling performance measure.
6. The method of claim 1, drilling at least a portion of a wellbore
based on the perturbed next best estimate.
7. The method of claim 1, wherein estimating, perturbing,
determining, perturbing, and feeding the perturbed next best
estimate are repeated until a gradient is less than a predetermined
threshold.
8. The method of claim 7, wherein the predetermined threshold is
zero.
9. A drilling system comprising: a drilling rig operable to form a
wellbore in a subterranean formation, the drilling rig having one
or more processors and a memory coupled therewith, the one or more
processors operable to execute instructions stored on the memory
that cause the cause the drilling system to: perturb a drilling
control parameter with a periodic or a stochastic signal during a
drilling process; estimate or calculating a drilling performance
measure to optimize the drilling process based on the perturbation
of the drilling control parameter; perturb the drilling performance
measure by multiplying the drilling performance measure with a
periodic or a stochastic perturbation source through demodulation;
determine a next best estimate of the drilling control parameter to
optimize the drilling performance measure; perturb the next best
estimate by a periodic or a stochastic perturbation source through
modulation; and feed the perturbed next best estimate of the
drilling control parameters to the drilling process.
10. The drilling system of claim 9, further comprising feed the
drilling performance measure through a high-pass filter.
11. The drilling system of claim 9, further comprising feed the
perturbed drilling performance measure through a low-pass
filter.
12. The drilling system of claim 9, wherein determine the next best
estimate comprises integrate a gradient to calculate the next best
estimate.
13. The drilling system of claim 9, wherein feed the next best
estimate to the drilling process includes adjust the one or more
drilling control parameters thus optimizing the selected at least
one drilling performance measure.
14. The drilling system of claim 9, drill at least a portion of a
wellbore based on the perturbed next best estimate.
15. The drilling system of claim 9, wherein estimate, perturb,
determine, perturbing, and feed the perturbed next best estimate
are repeated until a gradient is less than a predetermined
threshold.
16. The drilling system of claim 15, wherein the predetermined
threshold is zero.
17. A non-transitory computer-readable medium comprising executable
instructions, which when executed by a processor, causes the
processor to: perturb a drilling control parameter with a periodic
or a stochastic signal during a drilling process; estimate or
calculating a drilling performance measure to optimize the drilling
process based on the perturbation of the drilling control
parameter; perturb the drilling performance measure by multiplying
the drilling performance measure with a periodic or a stochastic
perturbation source through demodulation; determine a next best
estimate of the drilling control parameter to optimize the drilling
performance measure; perturb the next best estimate by a periodic
or a stochastic perturbation source through modulation; and feed
the perturbed next best estimate of the drilling control parameters
to the drilling process.
18. The non-transitory computer-readable medium of claim 17,
further comprising feed the drilling performance measure through a
high-pass filter.
19. The non-transitory computer-readable medium of claim 17,
further comprising feed the perturbed drilling performance measure
through a low-pass filter.
20. The non-transitory computer-readable medium of claim 17,
wherein estimate, perturb, determine, perturb, and feed the
perturbed next best estimate are repeated until a gradient is less
than a predetermined threshold.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of U.S. Provisional
Application No. 62/713,009, filed Aug. 1, 2018, the contents of
which are incorporated by reference herein in their entirety.
FIELD
[0002] The present technology is directed to a system and method
for drilling within a subterranean formation. In particular, the
present technology involves a system and method for drilling
optimization within a subterranean formation.
BACKGROUND
[0003] In an effort to extract hydrocarbons from subterranean
formation, drilling operations are undertaken to form a wellbore
through desirable portions of the subterranean formation. Drilling
operations are directed at the surface to control one or more
parameters in an attempt to maximize drilling efficiency and
accuracy. Controllable parameters can include rate of penetration
(ROP), weight on bit (WOB), and rotations per minute (RPM)
adjustable to achieve a particular set point for each individual
control parameter.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] The embodiments herein may be better understood by referring
to the following description in conjunction with the accompanying
drawings in which like reference numerals indicate analogous,
identical, or functionally similar elements. Understanding that
these drawings depict only exemplary embodiments of the disclosure
and are not therefore to be considered to be limiting of its scope,
the principles herein are described and explained with additional
specificity and detail through the use of the accompanying drawings
in which:
[0005] FIG. 1 is a schematic diagram of a drilling optimization
process according to the present disclosure;
[0006] FIG. 2 is a diagrammatic view of a drilling optimization
system according to the present disclosure;
[0007] FIG. 3A is a model of an extremum seeking method having ROP
maximized by controlling WOB and RPM according to the present
disclosure;
[0008] FIG. 3B is a result of an extremum seeking method having ROP
maximized by controlling WOB and RPM according to the present
disclosure;
[0009] FIG. 4 is a flow chart of a drilling optimization method
according to the present disclosure; and
[0010] FIG. 5 is a diagram of a computer device that can implement
various systems and methods discussed herein.
DETAILED DESCRIPTION
[0011] Various embodiments of the disclosure are discussed in
detail below. While specific implementations are discussed, it
should be understood that this is done for illustration purposes
only. A person skilled in the relevant art will recognize that
other components and configurations may be used without parting
from the spirit and scope of the disclosure. Additional features
and advantages of the disclosure will be set forth in the
description which follows, and in part will be obvious from the
description, or can be learned by practice of the herein disclosed
principles. The features and advantages of the disclosure can be
realized and obtained by means of the instruments and combinations
particularly pointed out in the appended claims. These and other
features of the disclosure will become more fully apparent from the
following description and appended claims, or can be learned by the
practice of the principles set forth herein.
[0012] The present disclosure is drawn to a new method for
optimizing a drilling operation within a subterranean formation.
The drilling optimization can target one or more drilling
performance measures (for example, ROP, mechanical specific energy
(MSE), torsional specific energy (TSE), or any combination thereof
in a cost function) and can include two main processes occurring at
different time scales: (i) a control parameter (for example, weight
on bit (WOB), torque on bit (TOB), revolutions per minute (RPM),
flow rate, choke, block height speed, draw-works speed, ROP, etc.)
estimation process and (ii) a gradient estimation process. The
control parameter estimation process is performed by an integrator
and the gradient estimation process handled by modulation and
demodulation of a feedback signal with a perturbation source. The
perturbation frequency can control the separation between the two
time scales.
[0013] The present disclosure includes methods and apparatuses for
a drilling optimization system during subterranean formation
drilling processes. The drilling optimization method, apparatus and
related system can be implemented on land-based and/or sea-based
drilling operations. While generally described and shown with
respect to a land-based operation, the present disclosure can be
similarly implemented in sea-based (e.g. off-shore) operations. In
offshore applications, block height speed control process can be
altered to include heave compensation.
[0014] The present disclosure targets optimization of a drilling
performance measure (e.g., ROP, MSE, TSE, or any combination
thereof). The present disclosure first estimates the drilling
performance for a given set of control parameters then evaluates
how to drive the input (e.g. control) parameters toward the
extremum of the cost function, if not yet reached.
[0015] The method can include perturbing one or more control
parameters with a periodic or stochastic signal during a drilling
process. The perturbation of the one or more control parameter can
allow control either automatically or manually of drilling system
actuators. The method can calculate and/or estimate at least one
drilling performance measurement during the drilling operation to
be optimized. The drilling performance measure can be fed through a
function performing a high-pass filter effect to eliminate the
direct current (DC) component of the signal. The drilling
performance measure can be perturbed (for example, multiplied) by a
periodic or stochastic perturbation source through demodulation
(for example, at substantially the same frequency as the
perturbation with respect to the one or more control parameters).
The perturbed (and filtered) signal can be fed through a function
performing a low-pass filter effect. The method can integrate the
gradient to calculate the next best estimate of the controlled
parameters to optimize the drilling performance measure. The
estimate can be perturbed by a periodic or stochastic perturbation
source through modulation (for example, at substantially the same
frequency as the demodulation of the drilling performance measure).
The perturbed estimate of control parameters can be fed back to the
drilling process, thus adjusting one or more drilling process
parameter to optimize drilling performance. The method can be
repeated with one or more control parameters and one or more
drilling performance measures continuously to maintain optimized
drilling performance.
[0016] The drilling process can pause (for example, to make pipe
connections), thus allowing the optimum control parameter settings
to be stored on a memory. Upon resuming of drilling, the control
parameters can be initialized at their optimized settings.
[0017] The optimized control parameter settings throughout the
entire drilling process can be stored in a non-volatile memory for
at least one of the following purposes: (i) post-job analysis (ii)
future well design and/or (iii) having the option to go back (e.g.
revert) to any previous control parameter setting.
[0018] FIG. 1 illustrates an optimization-while-drilling (OWD)
process according to at least one instance of the present
disclosure. A drilling process 100 can include one or more drilling
tools 11 and related equipment disposed on a surface 102 (or a
boat/platform in sea based-operations). One or more drilling tools
11 can be coupled with the distal end 12 of a drill string 10. A
drill bit 16 can be disposed at the distal end 12 of the drill
string 10 and be operable to form a wellbore 14 in a subterranean
formation 50. The wellbore 14 can have one or more vertical,
curved, and/or horizontal portions extending through one or more
portions of the subterranean formation 50. In at least one
instance, the wellbore 14 is formed through one or more pay zone
portions of the subterranean formation 50. The one or more pay
zones having a more desirable hydrocarbon production.
[0019] The drill string 10 can be operable to optimize drilling
performance during drilling processes either locally or through the
surface or through a remotely located drill optimization control
system 18. The drill string 10 or related drilling optimization
control system 18 can be operable to be controlled locally on the
drill string 10 by one or more drilling tools 11, controlled on the
surface 102, and/or controlled remotely to adjust one or more
drilling parameters including, but not limited to, control
parameters and drilling performance measures. While FIG. 1 shows
the drill optimization control system 18 disposed at the surface
102, it is within the scope of this disclosure to implement the
drilling optimization control system 18 locally on the drill string
10 or remotely off-site. In at least one instance, the drill
optimization control system 18 can include, but not limited to, one
or more processors, random access memory (RAM), and/or storage
medium. One or more control parameters of the drill string 10 can
be adjusted during drilling operations to improve one or more
drilling performance measures.
[0020] The drill string 10 can optimize a drilling performance
measure including, but not limited to ROP, MSE, TSE, or any
combination thereof utilizing one or more control parameters
including, but not limited to, Block Height Speed, WOB, TOB, RPM,
flow rate, and the like. The drill string 10 can adjust one or more
control parameters using perturbation to improve one or more
drilling performance measures.
[0021] FIG. 2 is a diagrammatic view representing a drilling
performance optimization process according to at least one instance
of the present disclosure. The dashed elements shown in FIG. 2
represent optional processes the can be implemented to improve the
control performance.
[0022] The drilling process 202 can have an input vector, u,
representing at least one drilling control parameter including, but
not limited to, Block Height Speed, WOB, TOB, RPM, flow rate, and
the like, and the output vector y represents at least one drilling
performance measure including, but not limited to, ROP, MSE, TSE,
and combinations thereof.
[0023] As the perturbation source 204, a periodic signal, such as a
sinusoidal can be used, Asin(wt), where w is the perturbation
frequency and A is the perturbation amplitude. A high w is
desirable to get better estimation of the gradient and to have
smaller influence from perturbing high order dynamics of the
drilling process. The smaller A is, the smaller the residual error
can be obtained at the extremum; however, it also brings the risk
of getting caught in a local extremum.
[0024] In other instances, a stochastic signal can be used as the
perturbation source 204.
[0025] In some instances, a high-pass filtering effect 206 (for
example, wash out filter) can be represented by f.sub.HPF(u). The
high-pass filtering effect can remove the DC gain from the signal,
y. In at least one instance, a simple high-pass filter such as:
d d t y ^ .eta. ( t ) + .omega. h y ^ .eta. ( t ) = d d t y ( t ) Y
.eta. ( s ) = s s + .omega. h Y ( s ) ( 1 ) ##EQU00001##
[0026] can be used, where, .omega..sub.h, is the cut-off frequency
of the high-pass filter. To achieve optimum DC gain elimination
performance .omega..sub.h should be selected smaller than
.omega..
[0027] In some instances, a low-pass filter effect 208 can be
represented by f.sub.LPF(y.sub..eta.), The low-pass filter effect
208 can better estimate the gradient, .xi.. In at least one
instance, a simple low-pass filter such as:
d d t .xi. ( t ) + .omega. l .xi. ( t ) = .omega. l y ^ .eta. ( t )
E ( s ) = .omega. l s + .omega. l Y .eta. ( s ) ( 2 )
##EQU00002##
can be used where, .omega..sub.1, is the cut-off frequency of the
low-pass filter.
[0028] The integration process 210, f.sub.1(.xi.) with a gain
vector, K, can be used to control the speed of convergence. A form
of the integrator is shown below:
u ^ = ( t ) = K .intg. 0 .infin. .xi. ( t ) d t U ^ ( s ) = K s E (
s ) ( 3 ) ##EQU00003##
The resulting best estimate for the controller parameter vector,
{circumflex over (.mu.)}, can be bounded at this stage by using an
integrator with upper and lower bounds. These bounds can be induced
by the operational limits of the drilling rig and/or the
directional tool implemented for the particular drilling operation.
As each drilling rig, drilling tool, and/or directional tool can
have varying operational limits, the bounds can vary based on tool
selection and/or implementation.
[0029] If there are multiple inputs to the drilling process, each
input can be perturbed with different amplitude and rate based on
numerical properties of the control parameters and physical
capabilities of the actuators.
[0030] FIG. 3A is an illustrative example of the control method. To
simulate a drilling process, a well-established relation between
WOB, RPM, and ROP can be used, where drilling dysfunctions
(founders and limiters) limits ROP. FIG. 3B represents the model
and the result of extremum seeking method, where ROP is maximized
by controlling WOB and RPM.
[0031] With respect to FIG. 3A, the relationships between ROP, RPM,
and WOB can be visualized along with the founders and limiters
including hole cleaning, hole instability, stickslip, whirl,
directional tendency, and/or weight transfer to bit. As can be
appreciated in FIG. 3A, increasing ROP can substantially linearly
increase WOB/RPM, and thus the founders and limiters can be
experienced.
[0032] As can be appreciated in FIG. 3B, ROP asymptotically
approaches a maximum by controlling the WOB and RPM over time. In
this illustrative instance, one or more control parameters (e.g.
WOB and/or RPM) can be implemented with a perturbation source with
a periodic or stochastic signal prior to beginning the drilling
process. At least one drilling performance measurement that is to
be optimized (e.g. ROP) can be calculated and/or estimated. The
drilling performance measurement can then be perturbed by a
periodic or stochastic perturbation source through demodulation at
substantially the same frequency as the perturbation source
implemented with respect to the one or more control parameters. A
gradient can be integrated to calculate a next best estimate of the
one or more controlled parameters to optimize the drilling
performance measurement. The next best estimate of the one or more
controlled parameters can be perturbed by a periodic through
modulation, and the perturbed next best estimate can be then be fed
and/or implemented with the drilling process. The process can be
repetitively implemented until the gradient is less than a
predetermined threshold (e.g. zero). The gradient can
asymptotically approach zero, as illustrated by FIG. 3B, with the
ROP iteratively changing (oscillating) as the control parameters
(RPM/WOB) are adjusted and the ROP approaches a hypothetical
maximum.
[0033] Referring to FIG. 4, a flowchart is presented in accordance
with an example method. The example method 400 is provided by way
of example, as there is a variety of ways to carry out the method
400. Each block shown in FIG. 4 represents one or more processes,
methods, or subroutines carried out in the example method 400.
Furthermore, the illustrated order of blocks is illustrative only
and the order of the blocks can change according to the present
disclosure. Additional blocks may be added or fewer blocks can be
utilized, without deviating from the present disclosure. The
example method 400 can begin at block 402.
[0034] At block 402, one or more control parameters can be
perturbed with a periodic or stochastic signal prior to entering
the drilling process. The method can proceed to block 404.
[0035] At block 404, at least one drilling performance measure can
be calculated and/or estimated to be optimized during the drilling
process. The method 400 can calculate and/or estimate the drilling
performance measure based on the one or more control parameter
perturbations from block 402. The method 400 can optionally proceed
to block 406 or block 408.
[0036] At block 406, the at least one drilling performance measure
can be fed through a high-pass filter to kill the DC component of
the signal. The method 400 can proceed to block 408.
[0037] At block 408, the at least one drilling performance measure
can be perturbed (multiplied) by a periodic or stochastic
perturbation source through demodulation. In at least one instance,
the perturbation occurs at the same frequency with the perturbation
in block 402. The method 400 can optionally proceed to block 410 or
block 412.
[0038] At block 410, the perturbed signal can be fed through a
low-pass filter effect. The perturbed signal can have been
previously filtered in block 406. The method 400 can proceed to
block 412.
[0039] At block 412, the gradient can be integrated to calculate
the next best estimate of the one or more controlled parameters to
optimize at least one drilling performance measure. The method 400
can proceed to block 414.
[0040] At block 414, the estimate calculated in block 412 can be
perturbed by a periodic or stochastic perturbation source through
modulation. In at least one instance, the perturbation occurs at
the same frequency with the perturbation in block 406. The method
400 can proceed to block 416.
[0041] At block 416, the perturbed estimates of the one or more
control parameters can be fed back to the drilling process. The
perturbed estimates of the one or more control parameters can
adjust the drilling process and drilling operation to optimize the
selected at least one drilling performance measure. The method 400
can proceed to block 418.
[0042] At block 418, blocks 404-418 can be repeated, as necessary,
until the gradient is less than a predetermined threshold. In at
least one instance, the predetermined threshold is approximately
zero. The repetition of blocks 404-418 can further refine the
optimization of the drilling process and drilling operation,
further improving optimization of the selected at least one
drilling performance measure.
[0043] Referring to FIG. 5, a detailed description of an example
computer device 500 is provided that can operably implement various
systems and methods discussed herein. The computer device can be
applicable to the drilling process 100 and/or one or more drilling
tools 11 and other computing or network devices. It will be
appreciated that specific implementations of these devices can be
of differing possible specific computing architectures, not all of
which are specifically discussed herein but will be understood by
those of ordinary skill in the art.
[0044] The computer device 500 can be a computing system capable of
executing a computer program product to execute a computer process.
Data and program files can be input to the computer device 500,
which reads the files and executes the programs therein. Some of
the elements of the computer device 500 are shown in FIG. 5,
including one or more hardware processors 502, one or more data
storage devices 504, one or more memory devices 508, and/or one or
more ports 508-510. Additionally, other elements that will be
recognized by those skilled in the art can be included in the
computer device 500 but are not explicitly depicted in FIG. 5 or
discussed further herein. Various elements of the computer device
500 can communicate with one another by way of one or more
communication buses, point-to-point communication paths, or other
communication means not explicitly depicted in FIG. 5.
[0045] The processor 502 can include, for example, a central
processing unit (CPU), a microprocessor, a microcontroller, a
digital signal processor (DSP), and/or one or more internal levels
of cache. There can be one or more processors 502, such that the
processor 502 comprises a single central-processing unit, or a
plurality of processing units capable of executing instructions and
performing operations in parallel with each other, commonly
referred to as a parallel processing environment.
[0046] The computer device 500 can be a conventional computer, a
distributed computer, or any other type of computer, such as one or
more external computers made available via a cloud computing
architecture. The presently described technology is optionally
implemented in software stored on the data stored device(s) 504,
stored on the memory device(s) 506, and/or communicated via one or
more of the ports 508-510, thereby transforming the computer device
500 in FIG. 5 to a special purpose machine for implementing the
operations described herein. Examples of the computer device 500
include personal computers, terminals, workstations, mobile phones,
tablets, laptops, personal computers, multimedia consoles, gaming
consoles, set top boxes, and the like.
[0047] The one or more data storage devices 504 can include any
non-volatile data storage device capable of storing data generated
or employed within the computer device 500, such as computer
executable instructions for performing a computer process, which
can include instructions of both application programs and an
operating system (OS) that manages the various components of the
computer device 500. The data storage devices 504 can include,
without limitation, magnetic disk drives, optical disk drives,
solid state drives (SSDs), flash drives, and the like. The data
storage devices 504 can include removable data storage media,
non-removable data storage media, and/or external storage devices
made available via a wired or wireless network architecture with
such computer program products, including one or more database
management products, web server products, application server
products, and/or other additional software components. Examples of
removable data storage media include Compact Disc Read-Only Memory
(CD-ROM), Digital Versatile Disc Read-Only Memory (DVD-ROM),
magneto-optical disks, flash drives, and the like. Examples of
non-removable data storage media include internal magnetic hard
disks, SSDs, and the like. The one or more memory devices 506 can
include volatile memory (e.g., dynamic random access memory (DRAM),
static random access memory (SRAM), etc.) and/or non-volatile
memory (e.g., read-only memory (ROM), flash memory, etc.).
[0048] Computer program products containing mechanisms to
effectuate the systems and methods in accordance with the presently
described technology can reside in the data storage devices 504
and/or the memory devices 506, which can be referred to as
machine-readable media. It will be appreciated that
machine-readable media can include any tangible non-transitory
medium that is capable of storing or encoding instructions to
perform any one or more of the operations of the present disclosure
for execution by a machine or that is capable of storing or
encoding data structures and/or modules utilized by or associated
with such instructions. Machine-readable media can include a single
medium or multiple media (e.g., a centralized or distributed
database, and/or associated caches and servers) that store the one
or more executable instructions or data structures.
[0049] In some implementations, the computer device 500 includes
one or more ports, such as an input/output (I/O) port 508 and a
communication port 510, for communicating with other computing,
network, or vehicle devices. It will be appreciated that the ports
508-510 can be combined or separate and that more or fewer ports
can be included in the computer device 500.
[0050] The I/O port 508 can be connected to an I/O device, or other
device, by which information is input to or output from the
computer device 500. Such I/O devices can include, without
limitation, one or more input devices, output devices, and/or
environment transducer devices.
[0051] In one implementation, the input devices convert a
human-generated signal, such as, human voice, physical movement,
physical touch or pressure, and/or the like, into electrical
signals as input data into the computer device 500 via the I/O port
508. Similarly, the output devices can convert electrical signals
received from computer device 500 via the I/O port 508 into signals
that can be sensed as output by a human, such as sound, light,
and/or touch. The input device can be an alphanumeric input device,
including alphanumeric and other keys for communicating information
and/or command selections to the processor 502 via the I/O port
1608. The input device can be another type of user input device
including, but not limited to: direction and selection control
devices, such as a mouse, a trackball, cursor direction keys, a
joystick, and/or a wheel; one or more sensors, such as a camera, a
microphone, a positional sensor, an orientation sensor, a
gravitational sensor, an inertial sensor, and/or an accelerometer;
and/or a touch-sensitive display screen ("touchscreen"). The output
devices can include, without limitation, a display, a touchscreen,
a speaker, a tactile and/or haptic output device, and/or the like.
In some implementations, the input device and the output device can
be the same device, for example, in the case of a touchscreen.
[0052] The environment transducer devices convert one form of
energy or signal into another for input into or output from the
computer device 500 via the I/O port 508. For example, an
electrical signal generated within the computer device 500 can be
converted to another type of signal, and/or vice-versa. In one
implementation, the environment transducer devices sense
characteristics or aspects of an environment local to or remote
from the computer device 500, such as, light, sound, temperature,
pressure, magnetic field, electric field, chemical properties,
physical movement, orientation, acceleration, gravity, and/or the
like. Further, the environment transducer devices can generate
signals to impose some effect on the environment either local to or
remote from the example computer device 500, such as, physical
movement of some object (e.g., a mechanical actuator), heating or
cooling of a substance, adding a chemical substance, and/or the
like.
[0053] In one implementation, a communication port 510 is connected
to a network by way of which the computer device 500 can receive
network data useful in executing the methods and systems set out
herein as well as transmitting information and network
configuration changes determined thereby. Stated differently, the
communication port 510 connects the computer device 500 to one or
more communication interface devices configured to transmit and/or
receive information between the computer device 500 and other
devices by way of one or more wired or wireless communication
networks or connections. Examples of such networks or connections
include, without limitation, Universal Serial Bus (USB), Ethernet,
Wi-Fi, Bluetooth.RTM., Near Field Communication (NFC), Long-Term
Evolution (LTE), and so on. One or more such communication
interface devices can be utilized via the communication port 1310
to communicate one or more other machines, either directly over a
point-to-point communication path, over a wide area network (WAN)
(e.g., the Internet), over a local area network (LAN), over a
cellular (e.g., third generation (3G) or fourth generation (4G))
network, or over another communication means. Further, the
communication port 510 can communicate with an antenna or other
link for electromagnetic signal transmission and/or reception.
[0054] In an example implementation, health data, air filtration
data, and software and other modules and services can be embodied
by instructions stored on the data storage devices 504 and/or the
memory devices 506 and executed by the processor 502. The computer
device 500 can be integrated with or otherwise form part of the
system for dynamic light adjustments.
[0055] The system set forth in FIG. 5 is but one possible example
of a computer system that can employ or be configured in accordance
with aspects of the present disclosure. It will be appreciated that
other non-transitory tangible computer-readable storage media
storing computer-executable instructions for implementing the
presently disclosed technology on a computing system can be
utilized.
[0056] In the present disclosure, the methods disclosed can be
implemented as sets of instructions or software readable by a
device (e.g., the computer device 500). Further, it is understood
that the specific order or hierarchy of steps in the methods
disclosed are instances of example approaches. Based upon design
preferences, it is understood that the specific order or hierarchy
of steps in the method can be rearranged while remaining within the
disclosed subject matter. The accompanying method claims present
elements of the various steps in a sample order, and are not
necessarily meant to be limited to the specific order or hierarchy
presented.
[0057] The embodiments shown and described above are only examples.
Even though numerous characteristics and advantages of the present
technology have been set forth in the foregoing description,
together with details of the structure and function of the present
disclosure, the disclosure is illustrative only, and changes may be
made in the detail, especially in matters of shape, size and
arrangement of the parts within the principles of the present
disclosure to the full extent indicated by the broad general
meaning of the terms used in the attached claims. It will therefore
be appreciated that the embodiments described above may be modified
within the scope of the appended claims.
Statement Bank
[0058] Statement 1: A method comprising: perturbing a drilling
control parameter with a periodic or a stochastic signal during a
drilling process; estimating or calculating a drilling performance
measure to optimize the drilling process based on the perturbation
of the drilling control parameter; perturbing the drilling
performance measure by multiplying the drilling performance measure
with a periodic or a stochastic perturbation source through
demodulation; determining a next best estimate of the drilling
control parameter to optimize the drilling performance measure;
perturbing the next best estimate by a periodic or a stochastic
perturbation source through modulation; and feeding the perturbed
next best estimate of the drilling control parameters to the
drilling process.
[0059] Statement 2: The method of Statement 1, further comprising
feeding the drilling performance measure through a high-pass
filter.
[0060] Statement 3: The method of Statement 1 or Statement 2,
further comprising feeding the perturbed drilling performance
measure through a low-pass filter.
[0061] Statement 4: The method of any one of Statements 1-3,
wherein determining the next best estimate comprises integrating a
gradient to calculate the next best estimate.
[0062] Statement 5: The method of any one of Statements 1-4,
wherein feeding next best estimate to the drilling process includes
adjusting the one or more drilling control parameters thus
optimizing the selected at least one drilling performance
measure.
[0063] Statement 6: The method of any one of Statements 1-5,
drilling at least a portion of a wellbore based on the perturbed
next best estimate.
[0064] Statement 7: The method of any one of Statements 1-6,
wherein estimating, perturbing, determining, perturbing, and
feeding the perturbed next best estimate are repeated until a
gradient is less than a predetermined threshold.
[0065] Statement 8: The method of any one of Statements 1-7,
wherein the predetermined threshold is zero.
[0066] Statement 9: A drilling system comprising: a drilling rig
operable to form a wellbore in a subterranean formation, the
drilling rig having one or more processors and a memory coupled
therewith, the one or more processors operable to execute
instructions stored on the memory that cause the cause the drilling
system to: perturb a drilling control parameter with a periodic or
a stochastic signal during a drilling process; estimate or
calculating a drilling performance measure to optimize the drilling
process based on the perturbation of the drilling control
parameter; perturb the drilling performance measure by multiplying
the drilling performance measure with a periodic or a stochastic
perturbation source through demodulation; determine a next best
estimate of the drilling control parameter to optimize the drilling
performance measure; perturb the next best estimate by a periodic
or a stochastic perturbation source through modulation; and feed
the perturbed next best estimate of the drilling control parameters
to the drilling process.
[0067] Statement 10: The drilling system of Statement 9, further
comprising feed the drilling performance measure through a
high-pass filter.
[0068] Statement 11: The drilling system of Statement 9 or
Statement 10, further comprising feed the perturbed drilling
performance measure through a low-pass filter.
[0069] Statement 12: The drilling system of any one of Statements
9-11, wherein determine the next best estimate comprises integrate
a gradient to calculate the next best estimate.
[0070] Statement 13: The drilling system of any one of Statements
9-12, wherein feed the next best estimate to the drilling process
includes adjust the one or more drilling control parameters thus
optimizing the selected at least one drilling performance
measure.
[0071] Statement 14: The drilling system of any one of Statements
9-13, drill at least a portion of a wellbore based on the perturbed
next best estimate.
[0072] Statement 15: The drilling system of any one of Statements
9-14, wherein estimate, perturb, determine, perturbing, and feed
the perturbed next best estimate are repeated until a gradient is
less than a predetermined threshold.
[0073] Statement 16: The drilling system of any one of Statements
9-15, wherein the predetermined threshold is zero.
[0074] Statement 17: A non-transitory computer-readable medium
comprising executable instructions, which when executed by a
processor, causes the processor to: perturb a drilling control
parameter with a periodic or a stochastic signal during a drilling
process; estimate or calculating a drilling performance measure to
optimize the drilling process based on the perturbation of the
drilling control parameter; perturb the drilling performance
measure by multiplying the drilling performance measure with a
periodic or a stochastic perturbation source through demodulation;
determine a next best estimate of the drilling control parameter to
optimize the drilling performance measure; perturb the next best
estimate by a periodic or a stochastic perturbation source through
modulation; and feed the perturbed next best estimate of the
drilling control parameters to the drilling process.
[0075] Statement 18: The non-transitory computer-readable medium of
Statement 17, further comprising feed the drilling performance
measure through a high-pass filter.
[0076] Statement 19: The non-transitory computer-readable medium of
Statement 17 or Statement 18, further comprising feed the perturbed
drilling performance measure through a low-pass filter.
[0077] Statement 20: The non-transitory computer-readable medium of
any one of Statements 17-19, wherein estimate, perturb, determine,
perturb, and feed the perturbed next best estimate are repeated
until a gradient is less than a predetermined threshold.
* * * * *