WO2016209265A1 - Identifying formation layer boundaries on well log measurements - Google Patents
Identifying formation layer boundaries on well log measurements Download PDFInfo
- Publication number
- WO2016209265A1 WO2016209265A1 PCT/US2015/037992 US2015037992W WO2016209265A1 WO 2016209265 A1 WO2016209265 A1 WO 2016209265A1 US 2015037992 W US2015037992 W US 2015037992W WO 2016209265 A1 WO2016209265 A1 WO 2016209265A1
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- WO
- WIPO (PCT)
- Prior art keywords
- well log
- log measurements
- derivative
- smoothing
- formation layer
- Prior art date
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- 238000005259 measurement Methods 0.000 title claims abstract description 112
- 230000015572 biosynthetic process Effects 0.000 title claims abstract description 57
- 238000009499 grossing Methods 0.000 claims abstract description 34
- 238000000034 method Methods 0.000 claims abstract description 32
- 230000005251 gamma ray Effects 0.000 claims description 7
- 238000005553 drilling Methods 0.000 claims description 4
- 238000005755 formation reaction Methods 0.000 description 45
- 239000007787 solid Substances 0.000 description 11
- 238000012545 processing Methods 0.000 description 7
- 238000001514 detection method Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 230000007812 deficiency Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V5/00—Prospecting or detecting by the use of ionising radiation, e.g. of natural or induced radioactivity
- G01V5/04—Prospecting or detecting by the use of ionising radiation, e.g. of natural or induced radioactivity specially adapted for well-logging
Definitions
- the present disclosure generally relates to systems and methods for identifying formation layer boundaries on well log measurements. More particularly, the present disclosure relates to systems and methods for identifying formation layer boundaries on well log measurements using a second derivative of the last iteratively smoothed well log measurements and a fluctuation index to determine the extent of smoothing.
- FIG. 1 is a flow diagram illustrating one embodiment of a method for implementing the present disclosure.
- FIG. 2 is a well log illustrating synthetic (simulated) resistivity well log measurements used as exemplary input for step 102 in FIG. 1.
- FIG. 3 is a first derivative well log illustrating a first derivative of the resistivity well log measurements in FIG. 2 and a first derivative of the last smoothed resistivity well log measurements in FIG. 2, which may be used in step 104 of FIG. 1.
- FIG. 4 is a second derivative well log illustrating a second derivative of the resistivity well log measurements in FIG. 2 and a second derivative of the last smoothed resistivity well log measurements in FIG. 2 at each sampled point, which may be used in step 114 of FIG. 1.
- FIGS. 5A-5B are two well logs illustrating real resistivity well log measurements at a predetermined depth in a well bore and a comparison of the formation layer boundaries displayed in step 118 of FIG. 1 (FIG. 5A) with the formation layer boundaries displayed according to the well-known variance based (FIG. 5B).
- FIGS. 6A-6B are two well logs illustrating real resistivity well log measurements at another predetermined depth in the same well bore and a comparison of the formation layer boundaries displayed in step 118 of FIG. 1 (FIG. 6 A) with the formation layer boundaries displayed according to the well-known variance based (FIG. 6B).
- FIGS. 7A-7B are two well logs illustrating real resistivity well log measurements at still another predetermined depth in the same well bore and a comparison of the formation layer boundaries displayed in step 118 of FIG. 1 (FIG. 7A) with the formation layer boundaries displayed according to the well-known variance based (FIG. 7B).
- FIGS. 8A-8D are well logs illustrating real gamma ray well log measurements at a predetermined depth in a well bore and a comparison of the formation layer boundaries displayed in step 118 of FIG. 1 at different resolutions.
- FIGS. 9A-9D are well logs illustrating real gamma ray well log measurements at a predetermined depth in a well bore and a comparison of the formation layer boundaries displayed in step 118 of FIG. 1 at different resolutions.
- FIG. 10 is a block diagram illustrating one embodiment of a computer system for implementing the present disclosure.
- the present disclosure overcomes one or more deficiencies in the prior art by providing systems and methods for identifying formation layer boundaries on well log measurements using a second derivative of the last iteratively smoothed well log measurements and a fluctuation index to determine the extent of smoothing.
- the present disclosure includes a method for identifying formation layer boundaries on well log measurements, which comprises: a) computing a first derivative using one of a first derivative of the well log measurements and last smoothed well log measurements; b) computing a fluctuation index by dividing the first derivative by the number of data points in the well log measurements; c) smoothing one of the well log measurements and the last smoothed well log measurements using a computer processor; d) repeating steps a) - c) until the fluctuation index is less than a predetermined threshold; e) computing a second derivative using one of a second derivative of the well log measurements and the last smoothed well log measurements at each sampled point; f) identifying each second derivative with a zero value, which represents an inflection point; and g) displaying a formation layer boundary on one of the well log measurements and the last smoothed well log measurements at each identified inflection point.
- the present disclosure includes a non-transitory program carrier device tangibly carrying computer executable instructions for identifying formation layer boundaries on well log measurements, the instructions being executable to implement: a) computing a first derivative using one of a first derivative of the well log measurements and last smoothed well log measurements; b) computing a fluctuation index by dividing the first derivative by the number of data points in the well log measurements; c) smoothing one of the well log measurements and the last smoothed well log measurements; d) repeating steps a) - c) until the fluctuation index is less than a predetermined threshold; e) computing a second derivative using one of a second derivative of the well log measurements and the last smoothed well log measurements at each sampled point; f) identifying each second derivative with a zero value, which represents an inflection point; and g) displaying a formation layer boundary on one of the well log measurements and the last smoothed well log measurements at each identified inflection point.
- the present disclosure includes a non-transitory program carrier device tangibly carrying computer executable instructions for identifying formation layer boundaries on well log measurements, the instructions being executable to implement: a) computing a first derivative using one of a first derivative of the well log measurements and last smoothed well log measurements; b) computing a fluctuation index by dividing the first derivative by the number of data points in the well log measurements; c) smoothing one of the well log measurements and the last smoothed well log measurements; d) repeating steps a) - c) until the fluctuation index is less than a predetermined threshold, wherein the predetermined threshold represents an optimal formation layer boundary resolution; e) computing a second derivative using one of a second derivative of the well log measurements and the last smoothed well log measurements at each sampled point; and f) identifying each second derivative with a zero value, which represents an inflection point.
- FIG. 1 a flow diagram illustrates one embodiment of a method 100 for implementing the present disclosure.
- the method 100 enables the display of a layer boundary on the last smoothed well log measurements where each respective second derivative value is equal to zero.
- the method 100 is based on a guided up-scaling of the data to be used for formation layer boundary detection.
- the up-scaling is adjusted automatically according to data resolution.
- step 102 well log measurements from a well bore and a predetermined formation layer boundary resolution are input using the client interface and/or the video interface described further in reference to FIG. 10.
- the well log measurements may comprise, for example, resistivity or gamma ray measurements.
- the predetermined formation layer boundary resolution is a parameter representing the thiclcness (resolution) of the formation layer boundaries displayed in step 118.
- a well log illustrates synthetic resistivity well log measurements that may be used as exemplary input.
- a first derivative (N) is computed using a first derivative of the well log measurements from step 102 or the last smoothed well log measurements from step 112, and techniques well known in the art.
- the first derivative (N) represents the number of peaks and troughs, which are also referred to as the number of zero crossings, in the first derivative of the well log measurements from step 102 or the last smoothed well log measurements from step 112.
- a first derivative well log illustrates a first derivative of the resistivity well log measurements in FIG. 2 and a first derivative of the last smoothed resistivity well log measurements in FIG. 2 as a result of step 112.
- a fluctuation index (FI) is computed by dividing the first derivative (N) from step 104 by the number of data points (M) in the well log measurements from step 102.
- step 108 the method 100 determines if FI from step 106 is less than a predetermined threshold representing the optimal thickness (resolution) of the formation layer boundaries displayed in step 118. If FI is less than a predetermined threshold, then the method 100 proceeds to step 114. Otherwise, the method 100 proceeds to step 110.
- a smoothing window size and a number of smoothing iterations are defined using FI from step 106 a predetermined scaling factor (SF) and a predetermined constant (C).
- the smoothing window size is equal to FI * SF and the number of smoothing iterations is equal to FI * C. The larger the smoothing window, the better (more smooth) the results.
- step 112 smoothing is performed on the well log measurements from step 102 or the last smoothed well log measurements from step 112 using the smoothing window size and number of smoothing iterations from step 110, and smoothing techniques well-known in the art.
- the method returns to step 104 and repeats steps 104-112 until FI is less than the predetermined threshold.
- a second derivative ( ⁇ ') is computed using a second derivative of the well log measurements from step 102 or the last smoothed well log measurements from step 112 at each sampled point, and techniques well-known in the art.
- the second derivative ( ⁇ ') thus, represents a value at each sampled point in the second derivative of the well log measurements from step 102 or the last smoothed well log measurements from step 112. If the second derivative ( ⁇ ') value is zero, then an inflection point is represented by the corresponding sampled point.
- a second derivative well log illustrates a second derivative of the resistivity well log measurements in FIG. 2 and a second derivative of the last smoothed resistivity well log measurements in FIG. 2 (as a result of step 112) at each sampled point.
- each second derivative ( ⁇ ') from step 114 with a zero value i.e. an inflection point
- ⁇ ' a zero value
- step 118 a formation layer boundary is displayed on the well log measurements from step 102 or the last smoothed well log measurements form step 112 at each inflection point identified in step 116 using the video interface described further in reference to FIG. 10.
- each solid horizontal line represents a formation layer boundary displayed according to the method 100.
- FIGS. 5A-5B two well logs illustrate real resistivity well log measurements (dashed lines) at a predetermined depth in a well bore and a comparison of the formation layer boundaries (solid horizontal lines) displayed in step 118 of FIG. 1 (FIG. 5A) with the formation layer boundaries (solid horizontal lines) displayed according to the well-known variance based (FIG. 5B).
- FIGS. 6A-6B two well logs illustrate real resistivity well log measurements (dashed lines) at another predetermined depth in the same well bore and a comparison of the formation layer boundaries (solid horizontal lines) displayed in step 118 of FIG. 1 (FIG. 6A) with the formation layer boundaries (solid horizontal lines) displayed according to the well- known variance based (FIG. 6B).
- FIGS. 7A-7B two well logs illustrate real resistivity well log measurements (dashed lines) at still another predetermined depth in the same well bore and a comparison of the formation layer boundaries (solid horizontal lines) displayed in step 118 of FIG. 1 (FIG. 7A) with the formation layer boundaries (solid horizontal lines) displayed according to the well-known variance based (FIG. 7B).
- the method 100 is capable of identifying more actual formation layer boundaries on well log measurements than the popular variance based method.
- the well logs illustrate real gamma ray well log measurements (dashed lines) at a predetermined depth in a well bore and a comparison of the formation layer boundaries (solid horizontal lines) displayed in step 118 of FIG. 1 at different resolutions.
- the well logs illustrate real gamma ray well log measurements (dashed lines) at a predetermined depth in a well bore and a comparison of the formation layer boundaries (solid horizontal lines) displayed in step 118 of FIG. 1 at different resolutions.
- the predetermined formation layer boundary resolution parameter in step 102 is capable of adjusting the thickness (resolution) of the formation layer boundaries displayed in step 118.
- the method 100 is thus, useful for interpretation and processing of different petrophysical and geophysical data that may lead to more efficient drilling operations through the adjustment of the same based on the location of the formation layer boundaries.
- the present disclosure may be implemented through a computer-executable program of instructions, such as program modules, generally referred to as software applications or application programs executed by a computer.
- the software may include, for example, routines, programs, objects, components and data structures that perform particular tasks or implement particular abstract data types.
- the software forms an interface to allow a computer to react according to a source of input.
- DecisionSpace ® which is a commercial software application marketed by Landmark Graphics Corporation, may be used as an interface application to implement the present disclosure.
- the software may also cooperate with other code segments to initiate a variety of tasks in response to data received in conjunction with the source of the received data.
- the software may be stored and/or carried on any variety of memory such as CD- ROM, magnetic disk, bubble memory and semiconductor memory (e.g. various types of RAM or ROM). Furthermore, the software and its results may be transmitted over a variety of carrier media such as optical fiber, metallic wire and/or through any of a variety of networks, such as the Internet.
- memory such as CD- ROM, magnetic disk, bubble memory and semiconductor memory (e.g. various types of RAM or ROM).
- the software and its results may be transmitted over a variety of carrier media such as optical fiber, metallic wire and/or through any of a variety of networks, such as the Internet.
- the disclosure may be practiced with a variety of computer-system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable-consumer electronics, minicomputers, mainframe computers, and the like. Any number of computer-systems and computer networks are acceptable for use with the present disclosure.
- the disclosure may be practiced in distributed-computing environments where tasks are performed by remote- processing devices that are linked through a communications network.
- program modules may be located in both local and remote computer- storage media including memory storage devices.
- the present disclosure may therefore, be implemented in connection with various hardware, software or a combination thereof, in a computer system or other processing system.
- FIG. 10 a block diagram illustrates one embodiment of a system for implementing the present disclosure on a computer.
- the system includes a computing unit, sometimes referred to as a computing system, which contains memory, application programs, a client interface, a video interface, and a processing unit.
- the computing unit is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the disclosure.
- the memory primarily stores the application programs, which may also be described as program modules containing computer-executable instructions, executed by the computing unit for implementing the present disclosure described herein and illustrated in FIGS. 1-9.
- the memory therefore, includes a formation layer boundary identification module, which enables steps 104-118 described in reference to FIG. 1.
- the formation layer boundary identification module may integrate functionality from the remaining application programs illustrated in FIG. 10.
- DecisionSpace ⁇ may be used as an interface application to perform step 102 in FIG. 1.
- DecisionSpace ® may be used as interface application, other interface applications may be used, instead, or the formation layer boundary identification module may be used as a stand-alone application.
- the computing unit typically includes a variety of computer readable media.
- computer readable media may comprise computer storage media and communication media.
- the computing system memory may include computer storage media in the form of volatile and/or nonvolatile memory such as a read only memory (ROM) and random access memory (RAM).
- ROM read only memory
- RAM random access memory
- a basic input/output system (BIOS) containing the basic routines that help to transfer information between elements within the computing unit, such as during start-up, is typically stored in ROM.
- the RAM typically contains data and/or program modules that are immediately accessible to, and/or presently being operated on, the processing unit.
- the computing unit includes an operating system, application programs, other program modules, and program data.
- the components shown in the memoiy may also be included in other removable/nonremovable, volatile/nonvolatile computer storage media or they may be implemented in the computing unit through an application program interface ("API") or cloud computing, which may reside on a separate computing unit connected through a computer system or network,
- API application program interface
- cloud computing which may reside on a separate computing unit connected through a computer system or network
- a hard disk drive may read from or write to nonremovable, nonvolatile magnetic media
- a magnetic disk drive may read from or write to a removable, nonvolatile magnetic disk
- an optical disk drive may read from or write to a removable, nonvolatile optical disk such as a CD ROM or other optical media.
- removable/nonremovable, volatile/nonvolatile computer storage media that can be used in the exemplary operating environment may include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like.
- the drives and their associated computer storage media discussed above provide storage of computer readable instructions, data structures, program modules and other data for the computing unit.
- a client may enter commands and information into the computing unit through the client interface, which may be input devices such as a keyboard and pointing device, commonly referred to as a mouse, trackball or touch pad. Input devices may include a microphone, joystick, satellite dish, scanner, or the like. These and other input devices are often connected to the processing unit through the client interface that is coupled to a system bus, but may be connected by other interface and bus structures, such as a parallel port or a universal serial bus (USB).
- USB universal serial bus
- a monitor or other type of display device may be connected to the system bus via an interface, such as a video interface.
- a graphical user interface may also be used with the video interface to receive instructions from the client interface and transmit instructions to the processing unit.
- computers may also include other peripheral output devices such as speakers and printer, which may be connected through an output peripheral interface.
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Abstract
Description
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Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
PCT/US2015/037992 WO2016209265A1 (en) | 2015-06-26 | 2015-06-26 | Identifying formation layer boundaries on well log measurements |
US15/026,564 US9874094B2 (en) | 2014-07-25 | 2015-06-26 | Identifying formation layer boundaries on well log measurements |
FR1654724A FR3037992B1 (en) | 2015-06-26 | 2016-05-26 | IDENTIFICATION OF TRAINING LAYER LIMITS ON WELL DIAGRAM MEASUREMENTS |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
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PCT/US2015/037992 WO2016209265A1 (en) | 2015-06-26 | 2015-06-26 | Identifying formation layer boundaries on well log measurements |
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WO2016209265A1 true WO2016209265A1 (en) | 2016-12-29 |
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PCT/US2015/037992 WO2016209265A1 (en) | 2014-07-25 | 2015-06-26 | Identifying formation layer boundaries on well log measurements |
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FR (1) | FR3037992B1 (en) |
WO (1) | WO2016209265A1 (en) |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4585939A (en) * | 1983-10-05 | 1986-04-29 | Halliburton Company | Multi-function natural gamma ray logging system |
US6466872B1 (en) * | 1999-11-08 | 2002-10-15 | Baker Hughes Incorporated | Method for determination of apparent resistivities of anisotropic reservoirs |
US6856909B2 (en) * | 2001-03-20 | 2005-02-15 | Shell Oil Company | Detecting a boundary in a formation |
US20060186887A1 (en) * | 2005-02-22 | 2006-08-24 | Strack Kurt M | Method for identifying subsurface features from marine transient controlled source electromagnetic surveys |
US20080015780A1 (en) * | 2006-03-30 | 2008-01-17 | Council Of Scientific And Industrial Research | Non-linear inversion technique for interpretation of geophysical data using analytically computed first and second order derivatives |
-
2015
- 2015-06-26 WO PCT/US2015/037992 patent/WO2016209265A1/en active Application Filing
-
2016
- 2016-05-26 FR FR1654724A patent/FR3037992B1/en not_active Expired - Fee Related
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4585939A (en) * | 1983-10-05 | 1986-04-29 | Halliburton Company | Multi-function natural gamma ray logging system |
US6466872B1 (en) * | 1999-11-08 | 2002-10-15 | Baker Hughes Incorporated | Method for determination of apparent resistivities of anisotropic reservoirs |
US6856909B2 (en) * | 2001-03-20 | 2005-02-15 | Shell Oil Company | Detecting a boundary in a formation |
US20060186887A1 (en) * | 2005-02-22 | 2006-08-24 | Strack Kurt M | Method for identifying subsurface features from marine transient controlled source electromagnetic surveys |
US20080015780A1 (en) * | 2006-03-30 | 2008-01-17 | Council Of Scientific And Industrial Research | Non-linear inversion technique for interpretation of geophysical data using analytically computed first and second order derivatives |
Also Published As
Publication number | Publication date |
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FR3037992B1 (en) | 2019-03-22 |
FR3037992A1 (en) | 2016-12-30 |
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