Method and device for preferably sorting entrapment and pre-exploratory well

Abstract

The invention provides a trap and pre-exploratory well optimization sorting method and device, and belongs to the technical field of oil exploration, and the method comprises the steps: obtaining first data of a to-be-optimized trap; based on the first data, performing first optimization on the first data of the to-be-optimized trap by adopting a preset optimization method, and determining the trap meeting a first preset standard as a target trap to be optimized by the pre-exploratory well; acquiring second data of the target trap; according to the second data, performing second optimization on the target trap by adopting a preset optimization method to obtain a pre-exploratory well optimization result; and sorting the pre-exploratory well optimization results to obtain a pre-exploratory well optimization sorting result. The device comprises a first data acquisition module, a trap optimization module, a second data acquisition module, a pre-exploratory well optimization module and a pre-exploratory well sorting module. According to the method, evaluation and optimal sorting of traps and pre-exploratory wells in different regions and fields according to a unified standard are realized, and the result is more objective.

Description

Technical Field

[0001] The present invention belongs to the field of petroleum exploration technology, and specifically relates to a method and device for optimizing and sorting traps and pre-exploration wells. Background Art

[0002] One of the main purposes of trap evaluation is to compare and analyze the evaluation results of multiple traps in a single platform in multiple directions and parameters, so as to select the trap with the greatest potential or the lowest risk and provide a basis for decision makers. There are many parameters for trap optimization decision-making. Different parameters can be used for queuing optimization, and then the optimization results can be comprehensively analyzed. In trap optimization, key parameters such as oil and gas probability, resource volume and net present value should be considered. Trap optimization is the purpose of trap evaluation and the prerequisite for the optimization of prospecting wells. Therefore, trap evaluation should strive to be accurate and reliable.

[0003] The existing trap optimization methods mainly include: (1) queuing method: queuing according to the resource volume (or net present value, expected return and internal rate of return) of the traps, giving priority to the most favorable traps; (2) chart method: by intersecting the resource volume, net present value, expected return or internal rate of return of multiple traps with the probability of oil and gas in the traps into a plane coordinate diagram, multiple traps are placed on the plane coordinate diagram, and the traps are classified by setting appropriate threshold conditions to optimize the traps; (3) Delphi method: comprehensive evaluation is carried out through expert scoring.

[0004] The most critical decision in oil and gas exploration is not which trap to drill, but which basin or zone to drill. The optimization of prospecting wells should not only consider the conditions of the traps, but also pay attention to their strategic significance. Therefore, the optimization of prospecting wells is based on the optimization of traps, comprehensively considering the probability of successful oil and gas exploration and the strategic value of drilling, and providing decision-makers with a basis for decision-making.

[0005] One of the methods for optimizing prospecting wells is to use the risk-value model, whose main factors are the probability of success and strategic value. The probability of success includes oil and gas risk and engineering and technical risk, and the strategic value includes the economic value of the closure and the strategic value coefficient. The optimization evaluation of prospecting wells can also use the Delphi method, that is, the expert scoring method. Different experts score the strategic significance and engineering and technical risks of prospecting wells separately, and finally take the evaluation value. Finally, the results of the two methods are combined, and different weights are assigned to them respectively and the weighted average is taken to weaken the influence of single factors and make a more objective evaluation of prospecting well optimization.

[0006] The various optimization methods for traps and prospecting wells mentioned above have problems such as inconsistent evaluation standards and parameter systems, unquantified value assignment standards, and inconsistent scoring scales, which lead to inaccurate evaluation and screening of traps and prospecting wells in different regions, fields, and resource types. Summary of the invention

[0007] Based on the above technical problems, the present application proposes a method and device for optimizing and sorting traps and prospecting wells.

[0008] In the first aspect, the present application proposes a method for optimizing and ranking traps and prospecting wells, comprising:

[0009] Acquiring first data of a trap to be optimally closed;

[0010] Based on the first data, a preset optimization method is used to perform a first optimization on the traps to be optimized, so as to obtain traps that meet the first preset standard, and the traps that meet the first preset standard are determined as the target traps to be optimized for the pre-exploration well;

[0011] Acquiring second data of the target trap;

[0012] Based on the second data, the target trap is optimized for the second time using the preset optimization method to obtain the optimization result of the pre-exploration well;

[0013] The preliminary exploration well optimization results are sorted to obtain the preliminary exploration well optimization sorting results.

[0014] The first data include: trap name, oil and gas probability, resource mean, resource with 10% probability, resource with 90% probability, trap evaluation value, net present value, expected return and internal rate of return.

[0015] After obtaining first data of the trap to be optimized, the method further includes: using the first data to create a parameter table, wherein each row of the parameter table represents a trap, and each column represents a data item of a trap;

[0016] After acquiring the second data of the target closure, the method further includes: adding the second data of the target closure to a corresponding column in the parameter table.

[0017] The preset optimization method includes: a hyperbola optimization method and / or a nine-square optimization method.

[0018] The hyperbolic optimization method comprises:

[0019] Draw a first plane rectangular coordinate system, wherein the x-axis represents the first drawing data, the y-axis represents the second drawing data, the first drawing data and the second drawing data are respectively one item of the first data or one item of the second data, and the first drawing data and the second drawing data are different items, and the point where the first drawing data and the second drawing data are both 0 is the origin of the first plane rectangular coordinate system;

[0020] In the first plane rectangular coordinate system, a hyperbola is drawn, the equation of the hyperbola is y=k / x, wherein k is the value of the hyperbola, which is determined by the value of x×y;

[0021] The data that meets the x-axis set threshold, the y-axis set threshold and is within the hyperbola opening is selected as the preferred data; alternatively, the data that meets the x-axis set threshold, the y-axis set threshold but is not within the hyperbola opening is selected as the preferred data; alternatively, the data that does not meet the x-axis set threshold, the y-axis set threshold but is within the hyperbola opening is selected as the preferred data.

[0022] The nine-square grid optimization method comprises:

[0023] Draw a second plane rectangular coordinate system, wherein the x-axis represents the first drawing data, the y-axis represents the second drawing data, the first drawing data and the second drawing data are respectively one item of the first data or one item of the second data, and the first drawing data and the second drawing data are different items, and the point where the first drawing data and the second drawing data are both 0 is the origin of the second plane rectangular coordinate system;

[0024] A first vertical line is drawn perpendicular to the x-axis using the maximum value of the first drawing data, a second vertical line is drawn perpendicular to the y-axis using the maximum value of the second drawing data, and a nine-square grid is drawn in a closed area surrounded by the first vertical line, the second vertical line, the x-axis, and the y-axis;

[0025] The first drawing data and the second drawing data are drawn in the nine-square grid, and the data in the nine-square grid are selected as the preferred data according to a preset preferred order.

[0026] The step of sorting the preliminary exploration well optimization results to obtain the preliminary exploration well optimization sorting results includes:

[0027] Sorting the optimization results of the prospecting wells by using chart sorting or R value sorting to obtain the optimization sorting results of the prospecting wells;

[0028] In the case where the preset optimization method is a hyperbola optimization method, the chart sorting includes: making a first parallel line to the y-axis through a threshold value set on the x-axis, making a second parallel line to the x-axis through a threshold value set on the y-axis, dividing a plurality of closed areas in a first plane rectangular coordinate system by the first parallel line, the second parallel line and the hyperbola, sorting the preliminary exploration well optimization results according to the first preset evaluation levels of the plurality of closed areas, and obtaining the preliminary exploration well optimization sorting results;

[0029] In the case where the preset optimization method is the nine-square grid optimization method, the plate sorting includes: sorting the preliminary exploration well optimization results according to the second preset evaluation levels of the nine areas in the nine-square grid to obtain the preliminary exploration well optimization sorting results;

[0030] The R value sorting is to sort the preliminary exploration well optimization results according to the size of the R value to obtain the preliminary exploration well optimization sorting results;

[0031] The R value calculation formula is as follows:

[0032]

[0033] Among them, R is the R value, val1 = (x-xmin) / (xmax-xmin), val2 = (y-ymin) / (ymax-ymin), xmax is the maximum value of all data on the x-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system, ymax is the maximum value of all data on the y-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system, xmin is the minimum value of all data on the x-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system, and ymin is the minimum value of all data on the y-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system.

[0034] In the second aspect, the present application proposes a device for optimizing the order of traps and pre-exploration wells, comprising:

[0035] A first data acquisition module, used to acquire first data to be optimally trapped;

[0036] A trap optimization module is used to perform a first optimization on the selected traps by using a preset optimization method based on the first data to obtain traps that meet a first preset standard, and determine the traps that meet the first preset standard as target traps to be selected for the prospecting well;

[0037] A second data acquisition module, used for second data of target closure;

[0038] A pre-exploration well optimization module is used to perform a second optimization on the target trap based on the second data by using the preset optimization method to obtain a pre-exploration well optimization result;

[0039] The pre-exploration well ranking module is used to sort the pre-exploration well optimization results to obtain the pre-exploration well optimization ranking results.

[0040] In a third aspect, the present application proposes an electronic device, comprising: a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the method for optimizing the order of closures and prospecting wells is executed.

[0041] In a fourth aspect, the present application provides a computer-readable storage medium storing executable instructions, which, when executed, enable a processor to execute the method for optimally ranking traps and prospecting wells.

[0042] Beneficial technical effects:

[0043] The present application proposes a method and device for optimizing and ranking closures and prospecting wells, which can achieve evaluation and optimization ranking of closures and prospecting wells in different regions and fields according to unified standards, and the results are more objective; more comprehensive screening and ranking conditions are provided, and a optimization method that better meets actual needs can be selected. The optimization method is more flexible and has higher operability and practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A method for optimizing and ranking traps and prospecting wells according to an embodiment of the present application;

[0045] Figure 2 A schematic diagram of a hyperbolic optimization method according to an embodiment of the present application;

[0046] Figure 3 A schematic diagram of a nine-square grid optimization method according to an embodiment of the present application;

[0047] Figure 4 A schematic diagram of selecting a filter type according to an embodiment of the present application;

[0048] Figure 5 This is a schematic diagram of the optimal queuing of the pre-exploration wells according to an embodiment of the present application;

[0049] Figure 6 This is a principle block diagram of a device for optimizing the sorting of traps and prospecting wells according to an embodiment of the present application. DETAILED DESCRIPTION

[0050] The present disclosure is further described below in conjunction with the embodiments shown in the accompanying drawings.

[0051] In view of the shortcomings of the existing optimization decision-making methods for closures and prospecting wells, in order to achieve the evaluation and optimization ranking of closures and prospecting wells in different regions and fields according to unified standards, obtain more objective results, provide more comprehensive screening and ranking conditions, support the selection of optimization methods that are more in line with actual needs, achieve adjustable screening thresholds and variable screening dimensions, and provide a more flexible optimization method with high operability and practicality, this application proposes a method and device for optimizing and ranking closures and prospecting wells, which achieves unified screening and ranking, and supports multiple screening and ranking methods to obtain more suitable optimization results.

[0052] Embodiment 1:

[0053] This embodiment proposes a method for optimizing the order of traps and prospecting wells, such as Figure 1 As shown, including:

[0054] Step S1: Acquire the first data to be optimally closed;

[0055] In this embodiment, the first data includes: trap name, oil and gas probability, resource mean, resource with 10% probability, resource with 90% probability, trap evaluation value, net present value, expected return and internal rate of return.

[0056] A parameter table is created using the acquired first data, wherein each row of the parameter table represents a closure, and each column represents a data item of a closure.

[0057] Step S2: Based on the first data, a preset optimization method is used to perform a first optimization on the traps to be optimized, so as to obtain traps that meet the first preset standard, and the traps that meet the first preset standard are determined as the target traps to be optimized for the prospecting well;

[0058] In this embodiment, the first optimization is performed based on the parameter table, and both the first optimization and the second optimization adopt a preset optimization method, including: a hyperbola optimization method and / or a nine-square grid optimization method. These two optimization methods will be described in detail later.

[0059] Step S3: Acquire the second data of the target enclosure;

[0060] Step S4: Based on the second data, the target trap is optimized for the second time using the preset optimization method to obtain the optimization result of the pre-exploration well;

[0061] In the specific implementation, the second data of the acquired target trap needs to be added to the corresponding column in the parameter table, so that the second optimization continues the parameter table used in the first optimization, and the evaluation and optimization ranking of traps and prospecting wells in different regions and fields are realized according to the unified standard.

[0062] Step S5: sorting the preliminary exploration well optimization results to obtain the preliminary exploration well optimization sorting results.

[0063] In this embodiment, the optimization results of the preliminary exploration wells are sorted by using a chart sorting or an R value sorting to obtain the optimization sorting results of the preliminary exploration wells;

[0064] In the case where the preset optimization method is the hyperbola optimization method, the optimization results of the pre-exploration wells are sorted by using a chart sorting method to obtain the optimization sorting results of the pre-exploration wells, and the chart sorting method includes: making a first parallel line of the y-axis through a threshold value set on the x-axis, making a second parallel line of the x-axis through a threshold value set on the y-axis, dividing a plurality of closed areas in a first plane rectangular coordinate system by the first parallel line, the second parallel line and the hyperbola, and sorting the optimization results of the pre-exploration wells according to the first preset evaluation levels of the plurality of closed areas to obtain the optimization sorting results of the pre-exploration wells;

[0065] In the case where the preset optimization method is the nine-square grid optimization method, the optimization results of the pre-exploration wells are sorted by using a chart sorting method to obtain the optimization results of the pre-exploration wells, and the chart sorting method includes: sorting the optimization results of the pre-exploration wells according to the second preset evaluation levels of the nine areas in the nine-square grid to obtain the optimization results of the pre-exploration wells;

[0066] The R value sorting is to sort the preliminary exploration well optimization results according to the size of the R value to obtain the preliminary exploration well optimization sorting results;

[0067] The R value calculation formula is as follows:

[0068]

[0069] Among them, R is the R value, val1 = (x-xmin) / (xmax-xmin), val2 = (y-ymin) / (ymax-ymin), xmax is the maximum value of all data on the x-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system, ymax is the maximum value of all data on the y-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system, xmin is the minimum value of all data on the x-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system, and ymin is the minimum value of all data on the y-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system.

[0070] The hyperbolic optimization method and the nine-square grid optimization method are described in detail below. The first optimization and the second optimization of the parameter table in this embodiment both adopt the hyperbolic optimization method and / or the nine-square grid optimization method.

[0071] The hyperbolic optimization method comprises:

[0072] Draw a first plane rectangular coordinate system, wherein the x-axis represents the first drawing data, the y-axis represents the second drawing data, the first drawing data and the second drawing data are respectively one item of the first data or one item of the second data, and the first drawing data and the second drawing data are different items, and the point where the first drawing data and the second drawing data are both 0 is the origin of the first plane rectangular coordinate system;

[0073] In the first plane rectangular coordinate system, a hyperbola is drawn, the equation of the hyperbola is y=k / x, wherein k is the value of the hyperbola, which is determined by the value of x×y;

[0074] The data that meets the x-axis set threshold, the y-axis set threshold and is within the hyperbola opening is selected as the preferred data; alternatively, the data that meets the x-axis set threshold, the y-axis set threshold but is not within the hyperbola opening is selected as the preferred data; alternatively, the data that does not meet the x-axis set threshold, the y-axis set threshold but is within the hyperbola opening is selected as the preferred data.

[0075] The nine-square grid optimization method comprises:

[0076] Draw a second plane rectangular coordinate system, wherein the x-axis represents the first drawing data, the y-axis represents the second drawing data, the first drawing data and the second drawing data are respectively one item of the first data or one item of the second data, and the first drawing data and the second drawing data are different items, and the point where the first drawing data and the second drawing data are both 0 is the origin of the second plane rectangular coordinate system;

[0077] A first vertical line is drawn perpendicular to the x-axis using the maximum value of the first drawing data, a second vertical line is drawn perpendicular to the y-axis using the maximum value of the second drawing data, and a nine-square grid is drawn in a closed area surrounded by the first vertical line, the second vertical line, the x-axis, and the y-axis;

[0078] The first drawing data and the second drawing data are drawn in the nine-square grid, and the data in the nine-square grid are selected as the preferred data according to a preset preferred order.

[0079] This embodiment proposes a method for optimizing and sorting traps and pre-exploration wells, which includes obtaining first data of traps to be optimized; based on the first data, performing a first optimization on the first data of the traps to be optimized using a preset optimization method, obtaining traps that meet a first preset standard, and determining the traps that meet the first preset standard as target traps to be optimized for pre-exploration wells; obtaining second data of the target traps; and performing a second optimization on the target traps using the same preset optimization method based on the second data, obtaining a pre-exploration well optimization result. This embodiment realizes unified screening and sorting of trap and pre-exploration well data, and supports multiple screening and sorting methods to obtain more appropriate optimization results.

[0080] Embodiment 2:

[0081] This embodiment is a specific example of the first embodiment. In the application of the specific example, a method for optimizing the sorting of traps and prospecting wells of the present application is described in detail.

[0082] This example takes into account the evaluation value of the engineering and technical risk of the pre-exploration well, the evaluation value of the success rate of the pre-exploration well, and the evaluation value of the strategic value. The closure and pre-exploration well optimization ranking method is used to obtain the pre-exploration well optimization ranking result. Finally, the investment in the pre-exploration well can be optimized based on the pre-exploration well optimization ranking result.

[0083] A method for optimizing and ranking traps and prospecting wells, comprising:

[0084] Step S100: Acquire first data to be optimally trapped;

[0085] In this embodiment, the first data obtained is used to create a parameter table. Each row of the parameter table represents a trap, and each column represents a data of a trap, as shown in Table 1. The table contains the name of each trap of the same level (the default is the third-level trap), the probability of oil and gas, the mean value of resources (the amount of resources in Table 1), the amount of resources P10 (i.e., the amount of resources with a probability of 10%), the amount of resources P90 (i.e., the amount of resources with a probability of 90%), the trap evaluation value, the net present value, the expected return, the internal rate of return, the trap screening box, and whether to participate in the evaluation.

[0086] Table 1 Parameters of the trap

[0087]

[0088] The first 8 columns of the parameter table (including: oil and gas probability, resources, resources P10, resources P90, net present value, expected return, internal rate of return) come from the calculation results of the trap evaluation, and are known external input data. Among them, the "Name" column comes from the basic data management in the trap evaluation; "Oil and gas probability" comes from the oil and gas evaluation results; "Resources", "Resources P10", and "Resources P90" come from the calculation results of resources; "Net present value", "Expected return", and "Internal rate of return" come from the economic evaluation results. In the last 3 columns, the "Evaluation value" (i.e., the trap evaluation value) is obtained by screening according to the hyperbolic optimization method or / and the nine-square optimization method; "Whether to screen" is obtained by screening or / and sorting by the hyperbolic optimization method or / and the nine-square optimization method, and can also be set manually, indicating the result after the trap optimization; "Participate in evaluation" is set manually by yourself, indicating whether to participate in the optimization or / and sorting.

[0089] Step S101: Based on the first data, a preset optimization method is used to perform a first optimization on the first data of the trap to be optimized, so as to obtain a trap that meets a first preset standard, and the trap that meets the first preset standard is determined as a target trap to be optimized for the prospecting well;

[0090] In this embodiment, both the first optimization and the second optimization adopt a preset optimization method, including: a hyperbola optimization method or / and a nine-square grid optimization method. In the first optimization, the hyperbola optimization method or / and the nine-square grid optimization method are used to remove the data corresponding to the closures that do not meet the first preset standard, and only retain the closures that meet the first preset standard. In this way, the decision-making process for the closures is completed, and the closures that meet the first preset standard are determined as the target closures to be selected for the pre-exploration well.

[0091] In order to sort and filter the data in the table parameter grid, a corresponding optimization chart is designed. Figure 2 , Figure 3As shown, the optimization map includes two modes: hyperbola optimization method and nine-square grid optimization method. Each row of data in the parameter table corresponds to a point in the map. Through interaction with the map, such as adjusting the hyperbola, setting the threshold on the x-axis, setting the threshold on the y-axis, etc., optimization sorting and regional division are performed, and the screening check boxes and order of each row in the parameter table are changed synchronously to achieve screening and sorting of these closures.

[0092] In this embodiment, the data in the parameter table is presented in a graphic form, and the graphic interaction is used to realize the optimization sorting. The resource volume (or net present value, expected return and internal rate of return) of multiple traps and the probability of oil and gas in the traps are intersected into a plane coordinate diagram, multiple traps are placed in the plane coordinate diagram, and the traps are classified by setting appropriate threshold conditions (resource volume x-axis setting threshold, resource volume y-axis setting threshold, oil and gas probability x-axis setting threshold, oil and gas probability y-axis setting threshold and hyperbola), so as to optimize the traps.

[0093] The optimization chart includes two modes: hyperbola optimization method and nine-square grid optimization method. Each row of data in the parameter table corresponds to a point on the chart. Through interaction with the chart, these closures are optimized and sorted. Among them, the hyperbola optimization method includes x-axis setting threshold, y-axis setting threshold, and hyperbola, which divides the chart into 4 areas. The nine-square grid optimization method divides the chart into 9 areas, and closures can be filtered and arranged by area. The x-axis setting threshold, y-axis setting threshold, and hyperbola can be dragged to adjust the position and modify the range of each area.

[0094] The hyperbolic optimization method comprises:

[0095] Draw a first plane rectangular coordinate system, wherein the x-axis represents the first drawing data, the y-axis represents the second drawing data, the first drawing data and the second drawing data are respectively one item of the first data or one item of the second data, and the first drawing data and the second drawing data are different items, and the point where the first drawing data and the second drawing data are both 0 is the origin of the first plane rectangular coordinate system;

[0096] In the first plane rectangular coordinate system, a hyperbola is drawn, the equation of the hyperbola is y=k / x, wherein k is the value of the hyperbola, which is determined by the value of x×y;

[0097] The data that meets the x-axis set threshold, the y-axis set threshold and is within the hyperbola opening is selected as the preferred data; alternatively, the data that meets the x-axis set threshold, the y-axis set threshold but is not within the hyperbola opening is selected as the preferred data; alternatively, the data that does not meet the x-axis set threshold, the y-axis set threshold but is within the hyperbola opening is selected as the preferred data.

[0098] Hyperbolic optimization method Figure 2 As shown, these traps (when the first optimization is performed Figure 2The data in the first well is the first data of the trap to be optimized) or the pilot well (when the second optimization is performed Figure 2 The data in the figure are the second data of the target trap) and are displayed in a two-dimensional coordinate graph. The point data in the graph come from each row of the parameter table. The left and right ends of the line segment are resource volume p90 and resource volume p10 respectively. When the x-axis is selected as resource volume, a line segment is drawn in the first plane rectangular coordinate system. In other cases, only points are drawn.

[0099] The x-axis and y-axis coordinate axis range is the range of all data corresponding points. After checking the origin, the range is the range of all data corresponding points plus the (0,0) point. Checking the logarithmic coordinate means switching the coordinate axis to logarithmic mode.

[0100] The diagram of the hyperbola optimization method contains three lines, the horizontal line (y-axis threshold setting) and the vertical line (x-axis threshold setting) are threshold values, and the curved line is a hyperbola, wherein the equation of the hyperbola is y=k / x, wherein k is the hyperbola value, which is determined by the value of x×y. The threshold value of the resource volume (or net present value, expected return and internal rate of return) is parallel to the ordinate axis, and the threshold value of the probability of oil and gas (or expected return) is parallel to the abscissa axis. Both can be moved, and can also be set through "adjusting X cutoff" and "adjusting Y cutoff", wherein "adjusting X cutoff" is to adjust the x-axis setting threshold, and "adjusting Y cutoff" is to adjust the y-axis setting threshold; in addition to setting the value through "adjusting hyperbola", the hyperbola can also be moved directly. The line segments parallel to the horizontal axis in the figure represent the distribution range of resource volume (or net present value, expected return, internal rate of return), the leftmost end is the corresponding value of resource volume P90, the rightmost end is the corresponding value of resource volume P10, the value corresponding to the dot on the line segment is the Swanson mean, and the name on the line segment is the trap name. The Swanson mean calculation formula is as follows:

[0101] P Swanson =0.3×P 90 +0.4×P 50 +0.3×P 10

[0102] Among them, P Swanson is the Swanson mean, P 90 is the resource volume with 90% probability, P 50 is the resource volume with 50% probability, P 10 is the resource volume with a probability of 10%, and 0.3 and 0.4 are fixed weights.

[0103] The three lines in the diagram of the hyperbola optimization method can be dragged to change or set values, and the first plane rectangular coordinate system is divided into different areas. Points falling in different areas can be displayed in different colors, and the corresponding rows in the parameter table also change the same color synchronously. The data is sorted according to the evaluation levels pre-set in multiple areas. The evaluation levels of each area from good to bad are as follows: if the data meets the x-axis set threshold, the y-axis set threshold, and is within the hyperbola opening, the color is RGB (0, 255, 0); if the data meets the x-axis set threshold, the y-axis set threshold, but is not within the hyperbola opening, the color is RGB (255, 170, 255); if the data does not meet the x-axis set threshold, the y-axis set threshold, but the data is within the hyperbola opening, the color is RGB (255, 255, 170); if the data does not meet the x-axis set threshold, the y-axis set threshold, and the data is not within the hyperbola opening, the color is RGB (255, 255, 170); if the x-axis set threshold and the y-axis set threshold are not met at the same time, and the data is not within the hyperbola opening, the color is RGB (255, 170, 170). The color of the point is consistent with the corresponding row in the parameter table.

[0104] Use the x-axis drop-down bar and y-axis drop-down bar to select the data in the corresponding column of the parameter table. When the first data is trapped for the first optimization, the x-axis drop-down bar includes "resource volume", "net present value", "expected return", "internal rate of return", and "probability of oil and gas × net present value". The y-axis drop-down bar includes "probability of oil and gas" and "expected return". You can switch the x-axis drop-down bar and y-axis drop-down bar, and redraw the points and three lines in the hyperbolic optimization method according to the selected content.

[0105] Check / uncheck x-axis logarithm and y-axis logarithm to indicate whether the x-value and y-value of the points in the graph are logarithmic. Check / uncheck logarithmic coordinates to indicate whether the coordinate axis is in logarithmic form. Check / uncheck origin start to indicate whether the coordinate axis starts from the origin. Check / uncheck show name to indicate whether the points in the graph are displayed with names. Check / uncheck show value to indicate whether the points in the graph are displayed with values.

[0106] The nine-square grid optimization method comprises:

[0107] Draw a second plane rectangular coordinate system, wherein the x-axis represents the first drawing data, the y-axis represents the second drawing data, the first drawing data and the second drawing data are respectively one item of the first data or one item of the second data, and the first drawing data and the second drawing data are different items, and the point where the first drawing data and the second drawing data are both 0 is the origin of the second plane rectangular coordinate system;

[0108] A first vertical line is drawn perpendicular to the x-axis using the maximum value of the first drawing data, a second vertical line is drawn perpendicular to the y-axis using the maximum value of the second drawing data, and a nine-square grid is drawn in a closed area surrounded by the first vertical line, the second vertical line, the x-axis, and the y-axis;

[0109] The first drawing data and the second drawing data are drawn in the nine-square grid, and the data in the nine-square grid are selected as the preferred data according to a preset preferred order.

[0110] In this embodiment, the diagram display mode can also be switched to a nine-square grid optimization mode, such as Figure 3 As shown in the figure, it is divided into 9 areas, and different areas are displayed in different shades of blue. The data is sorted according to the pre-set evaluation levels of multiple areas. The evaluation of each area is from good to bad in the following order: I1, I2, I3, II1, II2, II3, III1, III2, III3. The colors are from dark to light blue, and the bluest is RGB (0, 0, 255). Each time you go to the next area, the R and G values ​​increase by 255 or 9. The color of the point is consistent with the corresponding row in the parameter table. The nine-square grid line is obtained by dividing the data range of the x-axis and y-axis into three equal parts.

[0111] The data of each trap is displayed through a parameter table, and the preferred trap or prospecting well data is determined interactively through the hyperbola optimization method and / or the nine-square grid optimization method, which mainly includes two functions: screening and optimization sorting.

[0112] For the screening parameter table, the hyperbola optimization method mode and the nine-square grid optimization method mode pop up as follows Figure 4 The selection dialog box in the dialog box. Filter the enclosed table according to the selected conditions, keep those that meet the conditions, and filter out those that do not meet the conditions. Among them, there are 4 filtering conditions in the hyperbola optimization mode: ① Both the threshold setting and the hyperbola setting are met; ② The threshold setting is met, but the hyperbola setting is not met; ③ The threshold setting is not met, and the hyperbola setting is met; ④ Neither the threshold setting nor the hyperbola setting is met. There are 9 filtering conditions in the nine-square optimization mode: I1, I2, I3, II1, II2, II3, III1, III2, III3. After checking the combination of filtering conditions, the points in the area corresponding to the checked conditions will be checked in the "Whether to filter" column of the corresponding row in the table, and the remaining rows will be unchecked.

[0113] For the optimization sorting of the hyperbola optimization method mode and the nine-square grid optimization method mode, the data in the parameter table are sorted by plate sorting or R value sorting to obtain the optimization sorting result of the pre-exploration well; that is, the data is sorted from good to bad according to the regional evaluation. The R value optimization sorting is to sort the parameter table according to the evaluation value of the closure / pre-exploration well, that is, the evaluation value column in the parameter table is sorted from large to small.

[0114] Among them, the calculation method of the evaluation value, i.e., the R value in the parameter table, is as follows:

[0115] The total range of all points on the x-axis or y-axis of the chart in the hyperbola optimization method mode or the nine-square grid optimization method mode is counted, and the maximum value of the x-axis is recorded as xmax, the maximum value of the y-axis is recorded as ymax, the minimum value of the x-axis is recorded as xmin, and the minimum value of the y-axis is recorded as ymin;

[0116] For one of the traps / exploratory wells, its point coordinates on the map are recorded as (x, y);

[0117] First calculate the first value val1 and the second value val2 of the point (x, y);

[0118] Among them, val1=(x-xmin) / (xmax-xmin), val2=(y-ymin) / (ymax-ymin);

[0119] Then the evaluation value of this point (x, y) is

[0120] The above hyperbolic optimization method and / or nine-square grid optimization method can be used in the first optimization and the second optimization. The optimization sorting function can also be used as needed and is not limited to the one usage described in this embodiment.

[0121] Step S102: Acquire second data of target closure;

[0122] Step S103: Based on the second data, the target trap is optimized for the second time using the preset optimization method to obtain the optimization result of the pre-exploration well;

[0123] In the specific implementation, the second data of the acquired target trap needs to be added to the corresponding column in the parameter table, so that the second optimization continues the parameter table used in the first optimization, and the evaluation and optimization ranking of traps and prospecting wells in different regions and fields are realized according to the unified standard.

[0124] Preliminary well optimization is carried out on the basis of trap optimization decision. Before the preliminary well optimization is carried out, the trap optimization decision must be completed, that is, the trap that meets the first preset standard is determined as the target trap to be optimized for the preliminary well, and the trap optimization decision is completed; in this example, after the target trap to be optimized for the preliminary well is obtained, the second data of the target trap needs to be obtained, and the second data of the target trap includes: the engineering and technical risk, strategic value coefficient, preliminary well success rate and strategic value of the target trap to be optimized for the preliminary well.

[0125] The process of optimizing the exploration well is as follows: Figure 5 As shown in the figure, the optimization of prospecting wells is based on the above-mentioned method ideas, and several methods are integrated to provide a quick and convenient decision-making module for optimizing prospecting wells, which specifically includes:

[0126] Preliminary well optimization is carried out on the basis of trap optimization decision. Therefore, the trap optimization decision must be completed before the preliminary well optimization is carried out. The object of preliminary well optimization is favorable traps. The trap optimization decision is actually completed by using steps S100 to S101, which will not be repeated here. Among them, the operation process and interface of preliminary well optimization are similar to those of trap optimization. For the target traps participating in the preliminary well optimization (favorable traps in the trap optimization results, that is, traps that meet the first preset standard), it is necessary to obtain their engineering and technical risks and strategic value coefficients, and calculate the success rate and strategic value of the preliminary well.

[0127] Step S201: obtaining an initial parameter table for the optimal sorting of prospecting wells;

[0128] One of the methods for optimizing prospecting wells is to use the risk-value model, whose main factors are success probability and strategic value. The success probability includes: oil and gas risk and engineering technology risk, and the strategic value includes the economic value of the closure and the strategic value coefficient. The value assignment standards of each factor are shown in Table 2 and Table 3:

[0129] Table 2 Engineering technology risk probability assignment standards

[0130] Assignment Area Assignment basis (0.8,1.0] At present, engineering and process technologies are adapted to target exploration and development, and a series of supporting technologies has been formed. (0.6,0.8] Currently, engineering technology is more suitable for exploration and development, and some key technologies need to be improved. (0.4,0.6] Currently, a series of engineering process technologies are being formed, and some technologies still need to be tackled. [0,0.4] At present, engineering and process technologies cannot meet the requirements of exploration and development, and supporting technologies need to be improved on a large scale

[0131] Table 3 Probability Assignment Standards for Strategic Value Coefficients

[0132]

[0133] The parameter table for the optimization sorting of prospecting wells is shown in Table 4. The table contains the names of the traps of the same level (the default is the third-level trap), the probability of traps containing oil and gas, engineering and technical risks, expected returns, strategic value coefficients, success rates of prospecting wells, strategic values, prospecting well evaluation values, prospecting well screening boxes, and whether to participate in the evaluation. Each row of the table represents a third-level trap. The data columns displayed for the traps and prospecting well optimization are different. Only the traps that are checked in the previous trap screening step will appear in the prospecting well optimization.

[0134] Table 4 Parameter table for the optimal sorting of prospecting wells

[0135]

[0136] The three columns of data in the parameter table for the optimal sorting of prospecting wells, namely, "Name", "Probability of hydrocarbons in the trap", and "Expected return", are from the same source as those in the trap parameter table (i.e., Table 1). The evaluation values ​​in Table 4 are the calculation results of the known external input of the trap evaluation value. In this example, the calculation process of the success rate and strategic value of the prospecting wells is as follows:

[0137] The success rate of the pre-exploration well is calculated as follows:

[0138] V=Pog ×(1-R)

[0139] Among them, V is the success rate of the pre-exploration well, P og is the probability of containing oil and gas, and R is the engineering technical risk.

[0140] Strategic value, calculated as:

[0141] S=P r ×S r

[0142] Among them, S is the strategic value, Pr is the expected return, and Sr is the strategic value coefficient.

[0143] Step S202: weighted average according to a preset ratio to obtain a final parameter table for the optimal sorting of the prospecting wells;

[0144] In specific implementation, the opinions of expert evaluation can also be integrated, and the success rate and strategic value of the pre-exploration wells evaluated by experts and the success rate and strategic value of the pre-exploration wells calculated using the above calculation formula can be weighted averaged according to a preset ratio to obtain the final parameter table for the preferred ranking of pre-exploration wells.

[0145] Step S104: Based on the second data, the target trap is optimized for the second time using the preset optimization method to obtain the optimization result of the pre-exploration well;

[0146] The screening method of "preliminary well evaluation value" is the same as that of the closure evaluation value, and the hyperbola optimization method and / or the nine-square grid optimization method are used to obtain the preliminary well selection results; the "preliminary well screening box" is obtained by sorting and screening after the interactive chart, which is the same as the closure optimization method, and represents the preliminary well screening results; "participation in evaluation" is set by yourself, indicating whether to participate in the optimization sorting.

[0147] The first optimization and the second optimization use the same method, but the data processed are different. In the second optimization, the x-axis drop-down bar includes "strategic value" and "pre-exploration well success rate × value". The y-axis drop-down bar includes "pre-exploration well success rate" and "expected return". The data of the corresponding column in the table is drawn on the chart according to the x-axis and the content selected on the x-axis, and the filtering and sorting are realized through the interaction of the chart.

[0148] Step S105: sorting the preliminary exploration well optimization results to obtain preliminary exploration well optimization sorting results.

[0149] It is understandable that after the first optimization, the traps meeting the first preset standard can also be ranked by chart sorting or R value sorting, and the ranked traps meeting the first preset standard are determined as target traps to be selected for the pre-exploration well; finally, the pre-exploration well optimization results are still ranked by chart sorting or R value sorting to obtain the pre-exploration well optimization ranking results. Through two rounds of optimization and screening sorting, the final pre-exploration well optimization results and pre-exploration well optimization ranking results are obtained.

[0150] At this point, the process of trap and pilot well optimization is completed.

[0151] Although the embodiments disclosed in the present invention are as above, the above contents are only embodiments adopted for facilitating understanding of the present invention and are not intended to limit the present invention. The method of the present invention may also have other various embodiments. Without departing from the essence of the present invention, those skilled in the art may make various corresponding changes and deformations according to the present invention, but these corresponding changes and deformations shall all fall within the protection scope of the claims of the present invention.

[0152] This example proposes a method for optimizing and ranking closures and prospecting wells, which obtains the first data of the closures to be optimized, uses the hyperbola optimization method or / and the nine-square optimization method to optimize the first data for the first time, and determines the closures that meet the first preset standard as the target closures to be optimized for the prospecting wells; obtains the second data of the target closures; according to the second data, uses the hyperbola optimization method or / and the nine-square optimization method to optimize the target closures for the second time, and uses the plate sorting or R value sorting to sort the prospecting well optimization results to obtain the prospecting well optimization sorting results. This example realizes the evaluation and optimization sorting of closures and prospecting wells in different regions and fields according to unified standards, and the results are more objective; and it provides more comprehensive screening and sorting conditions, so that the optimization method that better meets actual needs can be selected; at the same time, it realizes adjustable screening thresholds and variable screening dimensions, and the optimization method is more flexible, with high operability and practicality.

[0153] Embodiment three:

[0154] This embodiment provides a device for optimizing the order of traps and prospecting wells, such as Figure 6 As shown, including:

[0155] A first data acquisition module, used to acquire first data to be optimally trapped;

[0156] A trap optimization module is used to perform a first optimization on the selected traps by using a preset optimization method based on the first data to obtain traps that meet a first preset standard, and determine the traps that meet the first preset standard as target traps to be selected for the prospecting well;

[0157] A second data acquisition module, used for second data of target closure;

[0158] A pre-exploration well optimization module is used to perform a second optimization on the target trap based on the second data by using the preset optimization method to obtain a pre-exploration well optimization result;

[0159] The pre-exploration well ranking module is used to sort the pre-exploration well optimization results to obtain the pre-exploration well optimization ranking results.

[0160] Embodiment 4:

[0161] This embodiment provides an electronic device, including: a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the method for optimally ranking traps and prospecting wells is executed.

[0162] The electronic device may be a mobile phone, a computer or a tablet computer, etc., including a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the trap and prospecting well optimization sorting method described in the embodiment is implemented. It is understood that the electronic device may also include an input / output (I / O) interface and a communication component.

[0163] The processor is used to execute all or part of the steps in the method for optimal sorting of traps and prospecting wells as described in the above embodiment. The memory is used to store various types of data, which may include instructions of any application or method in the electronic device, as well as data related to the application.

[0164] The processor may be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components, and is used to execute the trap and prospecting well optimization sorting method described in the above embodiment.

[0165] Embodiment five:

[0166] This embodiment provides a computer-readable storage medium storing executable instructions, which, when executed, enable a processor to execute the trap and prospecting well optimization sorting method.

[0167] If implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0168] Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method for optimizing the sorting of closures and prospecting wells described in each embodiment of the present application.

[0169] The aforementioned storage media include: flash memory, hard disk, multimedia card, card-type memory (for example, SD (Secure Digital Memory Card) or DX (Memory Data Register, MDR abbreviation, memory data register) memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, CD, server, APP (Application, abbreviation of application software) application store and other media that can store program verification codes, on which computer programs are stored. When the computer program is executed by the processor, the various steps of the above-mentioned method for optimizing the trap and prospecting wells can be implemented.

[0170] The various embodiments in the present disclosure are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0171] The protection scope of the present disclosure is not limited to the above-mentioned embodiments. Obviously, those skilled in the art can make various changes and modifications to the present disclosure without departing from the scope and spirit of the present disclosure. If these changes and modifications fall within the scope of the claims of the present disclosure and their equivalents, the intention of the present disclosure also includes these changes and modifications.

Claims

1. A method for optimizing and ranking traps and prospecting wells, characterized in that: include: Acquiring first data of a trap to be optimally closed; Based on the first data, a preset optimization method is used to perform a first optimization on the traps to be optimized, so as to obtain traps that meet the first preset standard, and the traps that meet the first preset standard are determined as the target traps to be optimized for the pre-exploration well; Acquiring second data of target closure; Based on the second data, the target trap is optimized for the second time using the preset optimization method to obtain the optimization result of the pre-exploration well; The preliminary exploration well optimization results are sorted to obtain the preliminary exploration well optimization sorting results.

2. The method for optimal sorting of traps and prospecting wells according to claim 1, characterized in that: The first data include: trap name, oil and gas probability, resource mean, resource with 10% probability, resource with 90% probability, trap evaluation value, net present value, expected return and internal rate of return.

3. The method for optimal sorting of traps and prospecting wells according to claim 1, characterized in that: After obtaining first data of the trap to be optimized, the method further includes: using the first data to create a parameter table, wherein each row of the parameter table represents a trap, and each column represents a data item of a trap; After acquiring the second data of the target closure, the method further includes: adding the second data of the target closure to a corresponding column in the parameter table.

4. The method for optimal sorting of traps and prospecting wells according to claim 3, characterized in that: The preset optimization method includes: a hyperbola optimization method and / or a nine-square optimization method.

5. The method for optimal sorting of traps and prospecting wells according to claim 4, characterized in that: The hyperbolic optimization method comprises: Draw a first plane rectangular coordinate system, wherein the x-axis represents the first drawing data, the y-axis represents the second drawing data, the first drawing data and the second drawing data are respectively one item of the first data or one item of the second data, and the first drawing data and the second drawing data are different items, and the point where the first drawing data and the second drawing data are both 0 is the origin of the first plane rectangular coordinate system; In the first plane rectangular coordinate system, a hyperbola is drawn, the equation of the hyperbola is y=k / x, wherein k is the value of the hyperbola, which is determined by the value of x×y; The data that meets the x-axis set threshold, the y-axis set threshold and is within the hyperbola opening is selected as the preferred data; alternatively, the data that meets the x-axis set threshold, the y-axis set threshold but is not within the hyperbola opening is selected as the preferred data; alternatively, the data that does not meet the x-axis set threshold, the y-axis set threshold but is within the hyperbola opening is selected as the preferred data.

6. The method for optimal sorting of traps and prospecting wells according to claim 4, characterized in that: The nine-square grid optimization method comprises: Draw a second plane rectangular coordinate system, wherein the x-axis represents the first drawing data, the y-axis represents the second drawing data, the first drawing data and the second drawing data are respectively one item of the first data or one item of the second data, and the first drawing data and the second drawing data are different items, and the point where the first drawing data and the second drawing data are both 0 is the origin of the second plane rectangular coordinate system; A first vertical line is drawn perpendicular to the x-axis using the maximum value of the first drawing data, a second vertical line is drawn perpendicular to the y-axis using the maximum value of the second drawing data, and a nine-square grid is drawn in a closed area surrounded by the first vertical line, the second vertical line, the x-axis, and the y-axis; The first drawing data and the second drawing data are drawn in the nine-square grid, and the data in the nine-square grid are selected as the preferred data according to a preset preferred order.

7. The method for optimally ranking traps and prospecting wells according to claim 5 or 6, characterized in that: The step of sorting the preliminary exploration well optimization results to obtain the preliminary exploration well optimization sorting results includes: Sorting the optimization results of the prospecting wells by using chart sorting or R value sorting to obtain the optimization sorting results of the prospecting wells; In the case where the preset optimization method is a hyperbola optimization method, the chart sorting includes: making a first parallel line to the y-axis through a threshold value set on the x-axis, making a second parallel line to the x-axis through a threshold value set on the y-axis, dividing a plurality of closed areas in a first plane rectangular coordinate system by the first parallel line, the second parallel line and the hyperbola, sorting the preliminary exploration well optimization results according to the first preset evaluation levels of the plurality of closed areas, and obtaining the preliminary exploration well optimization sorting results; In the case where the preset optimization method is the nine-square grid optimization method, the plate sorting includes: sorting the preliminary exploration well optimization results according to the second preset evaluation levels of the nine areas in the nine-square grid to obtain the preliminary exploration well optimization sorting results; The R value sorting is to sort the preliminary exploration well optimization results according to the size of the R value to obtain the preliminary exploration well optimization sorting results; The R value calculation formula is as follows: Among them, R is the R value, val1 = (x-xmin) / (xmax-xmin), val2 = (y-ymin) / (ymax-ymin), xmax is the maximum value of all data on the x-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system, ymax is the maximum value of all data on the y-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system, xmin is the minimum value of all data on the x-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system, and ymin is the minimum value of all data on the y-axis in the first plane rectangular coordinate system or the second plane rectangular coordinate system.

8. A device for optimizing the order of traps and prospecting wells, characterized in that: include: A first data acquisition module, used to acquire first data to be optimally trapped; A trap optimization module is used to perform a first optimization on the selected traps by using a preset optimization method based on the first data to obtain traps that meet a first preset standard, and determine the traps that meet the first preset standard as target traps to be selected for the prospecting well; A second data acquisition module, used for second data of target closure; A pre-exploration well optimization module is used to perform a second optimization on the target trap based on the second data by using the preset optimization method to obtain a pre-exploration well optimization result; The pre-exploration well ranking module is used to sort the pre-exploration well optimization results to obtain the pre-exploration well optimization ranking results.

9. An electronic device, characterized in that: include: A memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method for optimally sorting traps and prospecting wells according to any one of claims 1 to 7 is executed.

10. A computer-readable storage medium, characterized in that: The device stores executable instructions, which, when executed, enable the processor to execute the method for optimally sorting traps and prospecting wells as described in any one of claims 1 to 7.

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