US20180003007A1 - Selecting potential well location in a reservoir grid model - Google Patents

Selecting potential well location in a reservoir grid model Download PDF

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Publication number
US20180003007A1
US20180003007A1 US15/540,885 US201515540885A US2018003007A1 US 20180003007 A1 US20180003007 A1 US 20180003007A1 US 201515540885 A US201515540885 A US 201515540885A US 2018003007 A1 US2018003007 A1 US 2018003007A1
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Prior art keywords
grid
block
bounding box
surface grid
well location
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US15/540,885
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English (en)
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Feng Wang
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Landmark Graphics Corp
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Landmark Graphics Corp
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    • E21B41/0092—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
    • 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
    • E21B47/00—Survey of boreholes or wells
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • 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
    • E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V11/00—Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00

Definitions

  • the present disclosure generally relates to systems and methods for selecting potential well locations in a reservoir grid model. More particularly, the present disclosure relates to selecting potential well locations in a reservoir grid model using a bounding box with grid-block dimensions to calculate a total original gas-in-place (OGIP) and/or original oil-in-place (OOIP) for each bounding box associated with a potential well location.
  • OGIP original gas-in-place
  • OOIP original oil-in-place
  • An FDP is necessary before development of an oil or gas field may begin.
  • An FDP is based on a numerical reservoir simulation model also referred to as a reservoir grid model.
  • the reservoir grid model includes multiple grid-blocks of the same size and predetermined dimensions (DX, DY, DZ). Each grid-block includes information about the reservoir such as, for example, porosity for each grid block: ⁇ , initial water saturation for each grid block: Swi, and net to gross ratio for each grid block: NTG.
  • the reservoir grid model includes grid-block dimensions (i, j, k) that represent the number of grid-blocks in each dimension.
  • the main objective of the FDP is to optimize hydrocarbon recovery by determining the best number of potential wells, their type and location. Vertical wells are a natural first choice due to their ease of drilling, low cost and low risk.
  • FIGS. 1A-1B are a flow diagram illustrating one embodiment of a method for implementing the present disclosure.
  • FIG. 2 is a display of a partial reservoir grid model illustrating step 106 in FIG. 1A .
  • FIG. 3 is a display of a partial reservoir grid model illustrating steps 108 - 110 in FIG. 1A .
  • FIG. 4 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 selecting potential well locations in a reservoir grid model using a bounding box with grid-block dimensions to calculate a total original gas-in-place (OGIP) and/or original oil-in-place (OOIP) for each bounding box associated with a potential well location.
  • OGIP original gas-in-place
  • OOIP original oil-in-place
  • the present disclosure includes a method for selecting potential well locations in a reservoir, which comprises: a) selecting a bounding box with grid-block dimensions; b) selecting a surface grid-block for a potential well location in a reservoir grid model comprising multiple grid-blocks; c) positioning the bounding box around the surface grid-block; d) calculating a total original gas-in-place in the bounding box using an original gas-in-place for each grid-block in the bounding box; e) repeating steps b)-d) for each surface grid-block in the reservoir grid model using a computer processor; and f) selecting a largest total original gas-in-place calculated for a bounding box, which represents a bounding box with surface grid-block coordinates for a best well location.
  • the present disclosure includes a non-transitory program carrier device tangibly carrying computer-executable instructions for selecting potential well locations in a reservoir, the instructions being executable to implement: a) selecting a bounding box with grid-block dimensions; b) selecting a surface grid-block for a potential well location in a reservoir grid model comprising multiple grid-blocks; c) positioning the bounding box around the surface grid-block; d) calculating a total original gas-in-place in the bounding box using an original gas-in-place for each grid-block in the bounding box; e) repeating steps b)-d) for each surface grid-block in the reservoir grid model; and f) selecting a largest total original gas-in-place calculated for a bounding box, which represents a bounding box with surface grid-block coordinates for a best well location.
  • the present disclosure includes a non-transitory program carrier device tangibly carrying computer-executable instructions for selecting potential well locations in a reservoir, the instructions being executable to implement: a) selecting a bounding box; b) selecting a surface grid-block for a potential well location in a reservoir grid model comprising multiple grid-blocks; c) positioning the bounding box around the surface grid-block; d) calculating a total original gas-in-place in the bounding box using an original gas-in-place for each grid-block in the bounding box; e) repeating steps b)-d) for each surface grid-block in the reservoir grid model; f) selecting a largest total original gas-in-place calculated for a bounding box, which represents a bounding box with surface grid-block coordinates for a best well location; and g) selecting each total original gas-in-place calculated for a bounding box positioned around a surface grid-block that is within a predetermined number of surface grid-blocks from the surface grid-
  • a well drilled through grid-blocks with higher permeability and/or OGIP would have an anticipated higher production.
  • long-term performance of a well is more dependent on the OGIP connected to the well rather than on permeability.
  • permeability is usually positively correlated with porosity (or pore volume).
  • porosity or pore volume
  • FIGS. 1A-1B a flow diagram of one embodiment of a method 100 for implementing the present disclosure is illustrated.
  • a bounding box is automatically selected with grid-block dimensions (i, j, k).
  • the bounding box may be selected using the client interface and/or the video interface described further in reference to FIG. 4 .
  • the (i, j) grid-block dimensions are the same odd number representing a preferred length and width of the bounding box and the k grid-block dimension represents the depth of the bounding box that substantially corresponds to the grid-block depth of the reservoir grid model.
  • the (i, j) grid-block dimensions may be arbitrarily selected or they may be based on drainage area or trial and error.
  • any surface grid-block is selected for a potential well location in a reservoir grid model.
  • Any surface grid-block in the reservoir grid model may be selected as a potential well location because step 112 will repeat until every surface grid-block in the reservoir grid model has been selected for a potential well location.
  • only the surface grid-blocks are considered for potential well locations because the potential wells are vertical wells and each vertical well will pass through the same respective (i, j) grid-block coordinates in the reservoir grid model.
  • the bounding box selected in step 102 is positioned around the surface grid-block selected in step 104 so that one side of the bounding box is coterminous with an exterior side of the surface grid-block selected in step 104 and the surface grid-block is equidistant between the (i, j) grid-block dimensions of the bounding box.
  • a display 200 of a partial reservoir grid model may be used to illustrate this step.
  • the bounding box 202 is positioned around the surface grid-block 204 selected for a potential well location 206 . Only one side of the bounding box 202 is visible in the display 200 .
  • This side of the bounding box 202 is coterminous with an exterior side of the surface grid-block 204 and the surface grid-block 204 is equidistant between the (i, j) grid-block dimensions (5 ⁇ 5) of the bounding box 202 .
  • step 108 the OGIP is calculated for each grid-block in the bounding box positioned in step 106 .
  • OGIP DX*DY*DZ* ⁇ *NTG*(1-Swi) wherein each grid-block includes the same predetermined dimensions (DX, DY, DZ) and information about the reservoir such as, for example, porosity for each grid block: ⁇ , initial water saturation for each grid block: Swi, and net to gross ratio for each grid block: NTG.
  • a display 300 of a partial reservoir grid model may be used to illustrate this step.
  • the bounding box 302 is positioned around the surface grid-block 304 selected for a potential well location 306 .
  • the OGIP is calculated for each grid-block in the bounding box 302 , which includes (i, j) grid-block dimensions (5 ⁇ 5) and the k grid-block dimension 308 shown in an exploded view.
  • step 110 the total OGIP in the bounding box is calculated using the OGIP for each grid-block calculated in step 108 .
  • the OGIP for each grid-block in the bounding box 302 is summed for the total OGIP in the bounding box 302 .
  • step 112 the method 100 determines if there is another surface grid-block for a potential well location in the reservoir grid model. If there is another surface grid-block for a potential well location in the reservoir grid model, then the method 100 returns to step 104 to select another surface grid-block for a potential well location in the reservoir grid model. Otherwise, the method 100 proceeds to step 114 .
  • step 114 the total OGIP calculated in step 110 for each bounding box associated with a potential well location is ranked from largest to smallest or vice versa. Each surface grid-block selected for a potential well location in the reservoir grid model is thus, ranked in this manner.
  • step 116 the largest total OGIP from step 114 is selected, which represents the bounding box with the (i, j) surface grid-block coordinates for the best potential well location.
  • step 118 the method 100 determines if there is another total OGIP from step 114 that has not been selected in step 116 or step 124 . If there is not another total OGIP from step 114 that has not been selected, then the method 100 ends with the (i, j) surface grid-block coordinates for the best potential well location and, preferably, one or more (i, j) surface grid-block coordinates for the next best potential well location(s). It is possible, however, that the method 100 may end with only the (i, j) surface grid-block coordinates for the best potential well location. If there is another total OGIP from step 114 that has not been selected, then the method 100 proceeds to step 120 .
  • step 120 the next largest total OGIP from step 114 is identified.
  • step 122 the method 100 determines if the surface grid-block for the potential well location associated with the boundary box for the next largest total OGIP identified in step 120 is within a predetermined number of surface grid-blocks from the surface grid-block with the best potential well location selected in step 116 . If the surface grid-block for the potential well location associated with the boundary box for the next largest total OGIP identified in step 120 is not within a predetermined number of surface grid-blocks from the surface grid-block with the best potential well location selected in step 116 , then the method 100 returns to step 118 . Otherwise, the method 100 proceeds to step 124 .
  • a predetermined number of surface grid-blocks is used to prevent selected wells from clustering around areas with good reservoir properties. While the predetermined number of surface grid-blocks may be arbitrarily selected or may be based on the economics of drilling a well, at least two grid-blocks should be used because the selected wells would otherwise be too close for accurate reservoir simulation.
  • step 124 the next largest total OGIP identified in step 120 is selected, which represents the bounding box with the (i, j) surface grid-block coordinates for the next best potential well location.
  • the method 100 then returns to step 118 .
  • the results may be used to determine the type and number of wells in the FDP and, most importantly, their location to begin drilling operations. If, for example, there are ten potential well locations selected by the method 100 in a ranked order starting with the best, the next best and so on, the best two locations may be selected if the financial constraints are limited to two wells.
  • the bounding box size in step 102 and the predetermined number of surface grid-blocks i.e.
  • minimum well spacing in step 122 can be varied with each iteration of the entire method 100 to compare the differences, if any, and optimize the selection of the best potential well locations with highest potential oil and/or gas recovery.
  • the method 100 therefore, is very efficient and flexible for selecting the best potential well locations by using a bounding box and a predetermined minimum well spacing (i.e. predetermined number of surface grid-blocks).
  • the method 100 requires fewer simulation runs compared to conventional techniques. Only one simulation run is required for each iteration of the method 100 . In most cases, less than ten simulation runs are required to obtain the optimal potential well locations regardless of the number of potential well locations (i.e. grid-blocks). As a result, a lot of time can be saved for the design of an FDP.
  • One conventional well location optimization technique moves all 10 planned wells around each potential well location in the reservoir grid model.
  • One simulation run is required after every move of a well to a new potential well location. If each well has just 10 potential well locations, then the total number of simulation runs needed for a complete combination is 10 10 , which is ten billion. Even by using some advanced mathematical or statistical method like a neural network, a large number of simulation runs is still needed. Simulation time for such a reservoir size is typically 1 hour for a fast multi-CPU workstation, so the simulation time needed is cost and/or time prohibitive.
  • 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, data structures, etc., 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.
  • NexusTM which is commercial software application marketed by Landmark Graphics Corporation, may be used as 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.
  • Other code segments may provide optimization components including, but not limited to, neural networks, earth modeling, history-matching, optimization, visualization, data management, reservoir simulation and economics.
  • 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. 4 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. 1-3 .
  • the memory therefore, includes a potential well location selection module, which enables each step in FIGS. 1A-1B .
  • the potential well location selection module may integrate functionality from the remaining application programs illustrated in FIG. 4 .
  • NexusTM may be used as an interface application to supply the reservoir grid model used by the method 100 in FIGS. 1A-1B .
  • NexusTM may be used as interface application, other interface applications may be used, instead, or the potential well location selection 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 by the processing unit.
  • the computing unit includes an operating system, application programs, other program modules, and program data.
  • the components shown in the memory may also be included in other removable/non-removable, 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
  • a hard disk drive may read from or write to non-removable, 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/non-removable, 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, voice recognition or gesture recognition, 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 (“GUI”) may also be used with the video interface to receive instructions from the client interface and transmit instructions to the processing unit.
  • GUI graphical user interface
  • 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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US11680480B2 (en) 2021-05-25 2023-06-20 Saudi Arabian Oil Company Multi-layer gas reservoir field development system and method

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WO2019075242A1 (en) * 2017-10-11 2019-04-18 Beyond Limits, Inc. SYSTEM FOR IMPROVING EXPLORATION AND TANK PRODUCTION
CN110441815B (zh) * 2019-08-23 2021-05-25 电子科技大学 基于差分进化及块坐标下降的模拟退火瑞雷波反演方法

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US10294774B2 (en) * 2013-06-12 2019-05-21 Schlumberger Technology Corporation Well trajectory planning using bounding box scan for anti-collision analysis
US11680480B2 (en) 2021-05-25 2023-06-20 Saudi Arabian Oil Company Multi-layer gas reservoir field development system and method

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FR3033432A1 (es) 2016-09-09
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AR103602A1 (es) 2017-05-24
NO20171185A1 (en) 2017-07-14
CA2975437A1 (en) 2016-09-09
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GB2549910A (en) 2017-11-01
CA2975437C (en) 2019-09-10
AU2015384813A1 (en) 2017-08-10

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