IN A RESERVOIR GRID MODEL

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] Not applicable.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

[0002] Not applicable.

FIELD OF THE DISCLOSURE

[0003] 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.

BACKGROUND

[0004] In the oil and gas industry, a field development plan (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: φ, 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.

[0005] Reservoir simulation normally takes a long time to run especially for large reservoir grid models, Previous attempts require a large number of simulation runs no matter what advanced mathematical or statistical method is used, The reason is that every move of a potential well to a new location would warrant a new simulation run, For example, for a simple case with 2 wells to be optimized and 10 potential locations for each well, it would require 10x 10 = 100 simulation runs to investigate all possible combinations of well locations, For the optimization of a large number of wells, the number of the simulation runs needed is cost and/or time prohibitive,

BRIEF DESCRIPTION OF THE DRAWINGS

[0006] The present disclosure is described below with references to the accompanying drawings in which like elements are referenced with like reference numerals, and in which:

[0007] FIGS. 1A-1B, are a flow diagram illustrating one embodiment of a method for implementing the present disclosure,

[0008] FIG. 2. is a display of a partial reservoir grid model illustrating step 106 in FIG.

1A.

[0009] FIG. 3. is a display of a partial reservoir grid model illustrating steps 108-110 in FIG. 1A.

[0010] FIG. 4 is a block diagram illustrating one embodiment of a computer system for implementing the present disclosure.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[001 1] 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,

[0012] In one embodiment, 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.

[0013] In another embodiment, 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.

[0014] In yet another embodiment, 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-block with coordinates for the best well location.

[0015] The subject matter of the present disclosure is described with specificity; however, the description itself is not intended to limit the scope of the disclosure. The subject matter thus, might also be embodied in other ways, to include different steps or combinations of steps similar to the ones described herein, in conjunction with other present or future technologies. Moreover, although the term "step" may be used herein to describe different elements of methods employed, the term should not be inteipreted as implying any particular order among or between various steps herein disclosed unless otherwise expressly limited by the description to a particular order. While the present disclosure may be applied in the oil and gas industry, it is not limited thereto and may also be applied in other industries such as, for example, water or coal exploration to achieve similar results.

Method Description

[0016] Logically, a well drilled through grid-blocks with higher permeability and/or OGIP would have an anticipated higher production. For a conventional oil or gas reservoir, long-term performance of a well is more dependent on the OGIP connected to the well rather than on permeability. In addition, permeability is usually positively correlated with porosity (or pore volume). As such, the sum of OGIP for the grid-blocks to be penetrated by a potential well and the neighboring grid-blocks is an indicator of where the potential well should be located. In the following description, a gas field is chosen as the example for conciseness, but the method can also be applied to an oil field,

[0017] Referring now to FIGS. 1A-1B, a flow diagram of one embodiment of a method 100 for implementing the present disclosure is illustrated.

[0018] In step 102, a bounding box is automatically selected with grid-block dimensions (i, j, k). Alternatively, the bounding box may be selected using the client interface and/or the video interface described further in reference to FIG. 4. Preferably, 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 coiTesponds 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.

[0019] In step 104, 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. And, 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.

[0020] In step 106, 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. In FIG. 2, for example, 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 (5x5) of the bounding box 202.

[0021] In step 108, the OGIP is calculated for each grid-block in the bounding box positioned in step 106. OGIP=DX*DY*DZ*(|>*NTG*(l-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: φ, initial water saturation for each grid block: Swi, and net to gross ratio for each grid block: NTG. In FIG. 3, for example, 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 (5x5) and the k grid-block dimension 308 shown in an exploded view. [0022] In step 110, the total OGIP in the bounding box is calculated using the OGIP for each grid-block calculated in step 108. In FIG. 3, for example, the OGIP for each grid-block in the bounding box 302 is summed for the total OGIP in the bounding box 302.

[0023] In 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.

[0024] In 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.

[0025] In 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.

[0026] In 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.

[0027] In step 120, the next largest total OGIP from step 114 is identified.

[0028] In 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.

[0029] In 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.

[0030] When applied to an oil field, the method 100 will replace OGIP with OOIP=DX*DY*DZ*(S)*NTG*(l-Swi). At the end of the method 100, 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. Optionally, 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). And, 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.

[0031] Take for example, a typical reservoir grid model with grid-block dimensions 100x100x20 and 10 planned wells. 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. System Description

[0032] 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, Nexus™, 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.

[0033] Moreover, those skilled in the art will appreciate that 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. In a distributed- computing environment, 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.

[0034] Referring now to 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.

[0035] 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. In particular, Nexus™ may be used as an interface application to supply the reservoir grid model used by the method 100 in FIGS. 1A-1B. Although Nexus™ 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. [0036] Although the computing unit is shown as having a generalized memory, the computing unit typically includes a variety of computer readable media. By way of example, and not limitation, 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). A basic input/output system (BIOS), containing the basic routines that help to transfer information between elements within the computing unit, such as during startup, 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. By way of example, and not limitation, the computing unit includes an operating system, application programs, other program modules, and program data.

[0037] 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. For example only, 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, and an optical disk drive may read from or write to a removable, nonvolatile optical disk such as a CD ROM or other optical media, Other 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.

[0038] 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).

[0039] 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. In addition to the monitor, computers may also include other peripheral output devices such as speakers and printer, which may be connected through an output peripheral interface.

[0040] Although many other internal components of the computing unit are not shown, those of ordinary skill in the art will appreciate that such components and their interconnection are well known.

[0041] While the present disclosure has been described in connection with presently preferred embodiments, it will be understood by those skilled in the art that it is not intended to limit the disclosure to those embodiments. It is therefore, contemplated that various alternative embodiments and modifications may be made to the disclosed embodiments without departing from the spirit and scope of the disclosure defined by the appended claims and equivalents thereof.