Graph-based geological data evaluation method and device

Abstract

The invention relates to the technical field of geological data evaluation, and discloses a geological data evaluation method based on a chart, which comprises the following steps: acquiring experimental analysis data of a rock core, and determining an effective data range; selecting a proper data evaluation plate, enabling the plate to completely cover an effective data range through a method of prolonging classification lines and expanding the plate of the plate, and dividing the plate into a plurality of closed sub-regions which are not overlapped with one another and can cover all regions of the plate; according to each closed sub-region segmented by the plate, establishing a sub-region model, and determining a mapping relationship between each sub-region model and the evaluation result; and determining the evaluation result of the to-be-evaluated geological data through a domain-by-domain discrimination method based on the mapping relationship between the sub-region model and the evaluation result. The invention further discloses a geological data evaluation device based on the chart. According to the scheme, the geological data can be efficiently evaluated, the evaluation period is shortened, human resources are saved, and the requirements of quantitative statistics and comprehensive research of the geological data are met.

Description

Technical Field

[0001] The present invention relates to the technical field of geological data evaluation, and particularly to a method and device for evaluating geological data based on a chart. Background Art

[0002] The research work of oil and gas exploration and development usually needs to be completed with the help of many indicators, and a large amount of geological data may be involved in each indicator. Through years of research and experience accumulation, geologists have gradually formed a series of standards and charts for evaluating geological data. With the help of these standard and chart tools, we can conduct cluster analysis and data evaluation on geological data, and carry out comprehensive research based on this to guide oil and gas exploration and development. With the further in-depth research, researchers urgently hope to describe the research object more precisely, need to make qualitative or quantitative analysis on each data, and make accurate quantitative statistical analysis on the evaluation results of a large amount of data. However, there are the following problems in the actual evaluation work: the amount of data accumulated in the middle and late stages of exploration and development is very large, and the workload of accurately evaluating all data is extremely huge; after mapping the data into the chart, different data points cross and cover each other, interfering with the evaluation and statistics of the data; when the data points are near the chart decomposition line, it is very difficult to accurately judge the attribution of the data; making a macro and general evaluation of the data can no longer meet the needs of precise description, and it is difficult to make quantitative statistical analysis on the evaluation results of all data.

[0003] Therefore, there is a need to improve the method for evaluating geological data based on a chart in the prior art. Summary of the Invention

[0004] In view of this, the purpose of the embodiments of the present invention is to provide a method and device for evaluating geological data based on a chart, which can efficiently evaluate geological data, shorten the evaluation cycle, and save human resources to meet the needs of quantitative statistics and comprehensive research of geological data.

[0005] Based on the above purpose, on the one hand, an embodiment of the present invention provides a method for evaluating geological data based on a chart, including the following steps:

[0006] Obtain the experimental analysis data of the core and determine the effective data range of the experimental analysis data;

[0007] Select a suitable data evaluation chart in combination with the data characteristics and analysis purpose;

[0008] Extend the classification line in the chart so that the classification line can completely cover the effective data range;

[0009] Based on the extended chart classification line and the chart coordinate axis, divide the chart into several non-overlapping closed sub-regions that cover all regions of the chart;

[0010] For each closed sub-region segmented from the plate, establish a sub-region model respectively;

[0011] Determine the mapping relationship between each sub-region model and the evaluation result;

[0012] Based on the mapping relationship between the sub-region model and the evaluation result, determine the evaluation result of the geological data to be evaluated through the domain-by-domain discrimination method.

[0013] In some embodiments, determining the effective data range of the experimental analysis data includes:

[0014] Identify and eliminate invalid data in the experimental analysis data;

[0015] Obtain the effective data range recommended in the relevant evaluation criteria and materials;

[0016] Combining the effective data range recommended in the relevant evaluation criteria and materials, the regional geology, and the characteristics of the samples, comprehensively determine the effective data range.

[0017] In some embodiments, extending the classification lines in the plate so that the classification lines completely cover the effective data range includes:

[0018] Based on the effective data range, add auxiliary classification points to multiple classification lines in the plate, and sequentially extend the multiple classification lines in the plate to the corresponding auxiliary classification points;

[0019] Repeat the above steps until all classification lines intersect on the plate classification line or on the plate coordinate axis.

[0020] In some embodiments, for each closed sub-region segmented from the plate, establishing a sub-region model respectively includes:

[0021] Establish a sub-region model using a classification line function model or a scatter data fence model.

[0022] In some embodiments, establishing a sub-region model using a classification line function model or a scatter data fence model further includes:

[0023] The established sub-region model should completely match or have a matching degree greater than 98% with the closed sub-region to ensure that the established sub-region model can accurately describe the characteristics and morphology of the closed sub-region and finally obtain an accurate and reliable evaluation result; otherwise, if there is a deviation or non-matching between the established sub-region model and the closed sub-region, the evaluation result will be distorted or inaccurate;

[0024] When the number of plate classification lines is small and the shape of the plate classification line is a non-linear curve, preferably use a classification line function model to establish a sub-region model to ensure a high degree of matching between the established sub-region model and the closed sub-region;

[0025] When the number of plate classification lines is large or the shapes of the plate classification lines are all straight lines or line segments, a scatter data fence model is used to establish a sub-region model, so as to reduce the implementation difficulty while ensuring a high degree of coincidence between the established sub-region model and the closed sub-region.

[0026] In some embodiments, using the classification line function model to establish a sub-region model further includes:

[0027] Respectively determine the unique mapping relationship of the variable data on each extended classification line on the plate;

[0028] Select multiple anchor points on the extended plate classification line, and densely select anchor points at the places where the curve trend of the classification line changes violently;

[0029] Based on the plate coordinate axes, determine the accurate coordinates of multiple anchor points;

[0030] Based on multiple anchor points on each plate classification line, establish a function model to fit the extended classification line, and form several classification line function models.

[0031] In some embodiments, respectively determining the unique mapping relationship of the variable data on each extended classification line on the plate includes:

[0032] In response to being unable to determine the unique mapping relationship of the variable data on the plate classification line, the plate classification line is divided into multiple sub-classification lines, and the unique mapping relationship of the variable data is determined on the multiple sub-classification lines.

[0033] In some embodiments, using the scatter data fence model to establish a sub-region model further includes:

[0034] Select multiple anchor points on the edge of each closed sub-region. When there are many edge inflection points or the edge is a curve, densely select anchor points at the inflection points and the places where the curve trend changes violently;

[0035] Based on the plate coordinate axes, determine the accurate coordinates of multiple anchor points;

[0036] Take the anchor point coordinates on the edge of each non-overlapping closed sub-region as a set respectively. The polygon model formed by the anchor points and the connecting lines of the anchor points within each set is the scatter data fence model.

[0037] In some embodiments, based on the mapping relationship between the plate sub-region separation model and the evaluation result, determining the evaluation result of the geological data to be evaluated by the domain-by-domain discrimination method includes:

[0038] Determine the evaluation result of the geological data to be evaluated by the domain-by-domain discrimination method based on the classification line function model or the scatter data fence model.

[0039] In some embodiments, determining the evaluation result of geological data to be evaluated based on the domain-by-domain discrimination method of the classification line function model includes:

[0040] Using the curve of the classification line function model as the boundary to divide the plate;

[0041] Determining the evaluation order of geological data within each sub-region of the plate;

[0042] Based on the geological data mapping relationship, the plate classification line function model, and the evaluation order of geological data within the sub-region of the plate, calculating the numerical value of geological data on the plate classification line;

[0043] Comparing the numerical value of geological data on the plate classification line with the numerical value of the geological data to be evaluated, determining the sub-region model to which the geological data to be evaluated belongs, and obtaining the evaluation result of the geological data according to the mapping relationship between the sub-region model and the evaluation result;

[0044] Repeating the above steps until the evaluation results of all geological data are obtained.

[0045] In some embodiments, determining the evaluation result of geological data to be evaluated based on the domain-by-domain discrimination method of the scatter data fence model includes:

[0046] For each geological data, randomly construct a straight line passing through the geological data. If the straight line passes through any anchor point in the scatter data fence model, then randomly construct a straight line passing through the geological data until the constructed straight line does not pass through any anchor point in the scatter data fence model. Denote the equation of this straight line as:

[0047] Ax + By + C = 0

[0048] Using the data point as an endpoint and extending it in any direction on the straight line to form a ray;

[0049] Calculating the intersection points of the ray and the connecting lines of all adjacent anchor points in each scatter data fence model, and counting the number of intersection points;

[0050] Extracting the scatter data fence models with an odd number of intersection points;

[0051] Obtaining the evaluation result corresponding to the extracted scatter data fence model according to the mapping relationship between the sub-region model and the evaluation result, that is, obtaining the evaluation result of the geological data;

[0052] Repeating the above steps until the evaluation results of all geological data are obtained.

[0053] In some embodiments, calculating the intersection points of the ray and the connecting lines of all adjacent anchor points in each scatter data fence model and counting the number of intersection points includes:

[0054] Calculate the equations of the straight lines formed by any two adjacent anchor points in the scatter data fence model in sequence, denoted as:

[0055] ax + by + c = 0

[0056] Calculate the solution of the system of equations composed of Ax + By + C = 0 and ax + by + c = 0, which is the intersection coordinates of the two straight lines;

[0057] Check the position of the intersection point. If the intersection coordinates are within the ray coordinate range and the intersection point is within the coordinate range of the two anchor points on the connecting line of adjacent anchor points, it is determined that the intersection point is on the connecting line of the anchor points, triggering the intersection counting; otherwise, it is determined that the ray does not intersect with the connecting line of the anchor points.

[0058] Repeat the above steps until the statistical result of the number of intersection points between the ray and all the connecting lines of the anchor points is obtained.

[0059] On the other hand, the present invention also provides a geological data evaluation device based on a graph plate, including:

[0060] A data acquisition module configured to acquire the experimental analysis data of the core and determine the effective data range of the experimental analysis data;

[0061] A graph plate establishment module configured to select a suitable data evaluation graph plate in combination with the data characteristics and analysis purposes, and make the graph plate fully cover the effective data range by extending the classification line and expanding the graph plate method of the graph plate, and divide the graph plate into several non-overlapping closed sub-regions that can cover all regions of the graph plate;

[0062] A model establishment module configured to establish a sub-region model for each closed sub-region segmented from the graph plate respectively, and determine the mapping relationship between each sub-region model and the evaluation result;

[0063] A data evaluation module configured to determine the evaluation result of the geological data to be evaluated based on the mapping relationship between the sub-region model and the evaluation result by the domain-by-domain discrimination method.

[0064] The present invention has at least the following beneficial technical effects:

[0065] The method of the present invention determines the evaluation result of the geological data to be evaluated through the domain-by-domain discrimination method based on the classification line function model or the scatter data fence model, provides an implementation path for the program to automatically and batch quickly evaluate the geological data, helps to efficiently evaluate the geological data, shorten the evaluation cycle, and save human resources, and can provide a useful reference for the fine evaluation, quantitative statistics and comprehensive research of the geological data.

[0066] The device of the present invention has the same beneficial effects as described above. Brief Description of the Drawings

[0067] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other embodiments can be obtained based on these drawings.

[0068] Figure 1 Schematic diagram of an embodiment of the plate-based geological data evaluation method provided by the present invention;

[0069] Figure 2 HI-Tmax organic matter type plate provided by the present invention;

[0070] Figure 3 HI-Tmax organic matter type plate with the classification line extended in the present invention;

[0071] Figure 4 Schematic diagram of the anchor points for establishing the sub-region model using the classification line function model;

[0072] Figure 5 Schematic diagram of the anchor points for establishing the sub-region model using the scatter data fence model;

[0073] Figure 6 HI-Tmax organic matter type plate with geological data added provided by the present invention;

[0074] Figure 7 Schematic diagram for calculating the number of intersection points of the ray and each scatter data fence model;

[0075] Figure 8 Schematic diagram of an embodiment of the plate-based geological data evaluation device provided by the present invention. Detailed implementation manners

[0076] To make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the following further elaborates on the embodiments of the present invention in detail with reference to specific embodiments and the accompanying drawings.

[0077] It should be noted that all the expressions using "first" and "second" in the embodiments of the present invention are used to distinguish two entities or parameters with the same name but different, so "first" and "second" are only for the convenience of expression and should not be construed as a limitation on the embodiments of the present invention. This will not be elaborated one by one in the subsequent embodiments.

[0078] Based on the above objectives, in the first aspect of the embodiments of the present invention, an embodiment of the plate-based geological data evaluation method is proposed. Figure 1Shown is a schematic diagram of an embodiment of the plate-based geological data evaluation method provided by the present invention. As Figure 1 shown, the plate-based geological data evaluation method of the embodiment of the present invention includes the following steps:

[0079] S1 Obtain the experimental analysis data of the core and determine the effective data range of the experimental analysis data;

[0080] S2 Combine the data characteristics and analysis purposes to select a suitable data evaluation plate;

[0081] S3 Extend the classification line in the plate so that the classification line can completely cover the effective data range;

[0082] S4 Based on the extended plate classification line and the plate coordinate axis, divide the plate into several non-overlapping closed sub-regions that can cover all regions of the plate;

[0083] S5 According to each closed sub-region divided by the plate, establish a sub-region model respectively;

[0084] S6 Determine the mapping relationship between each sub-region model and the evaluation result;

[0085] S7 Based on the mapping relationship between the sub-region model and the evaluation result, determine the evaluation result of the geological data to be evaluated by the domain-by-domain discrimination method.

[0086] Further, in S1, obtain the pyrolysis experimental analysis data of the shale core. In some embodiments, obtain 200 to 300 data values. By screening and removing the invalid data in the experimental data, obtaining the effective data range recommended in the relevant evaluation criteria and materials, and combining the effective data range recommended in the relevant evaluation criteria and materials, regional geology and sample characteristics, comprehensively determine the well number, well depth, formation, Tmax, HI, and define the effective data range of Tmax and HI.

[0087] Further, in S2, based on the needs of oil and gas geochemical research, select the HI-Tmax organic matter type plate of the three-category four-division method to establish a data organic matter type evaluation plate, and determine the vitrinite reflectance Ro reference line in the data evaluation plate.

[0088] Further, in S3, based on the valid data range, auxiliary classification points are added to multiple classification lines of the plate, and the multiple classification lines of the plate are successively extended to the corresponding auxiliary classification points. The extended classification lines are also collectively referred to as classification lines hereinafter. The plate includes four classification lines. Extending the classification lines in the plate based on the valid data range includes: adding at least one auxiliary classification point to each classification line and successively extending the multiple classification lines of the plate to the corresponding auxiliary classification points. In some embodiments, if the existing plate cannot completely cover the determined valid data range, the existing plate should be expanded according to the research results until the plate can completely cover the valid data range.

[0089] Further, in S4, based on the extended classification lines of the plate and the plate coordinate axes, the plate is divided into 4 non-overlapping closed sub-regions that can cover all regions of the plate. The regions of the plate from bottom to top are Region III, Region II2, Region II1, and Region I (including the blank region in the upper right).

[0090] Further, in S5, for each closed sub-region segmented from the plate, a sub-region model is established respectively, including: establishing the sub-region model by using a classification line function model or a scatter data fence model. The established sub-region model should exactly match the closed sub-region or the matching degree should be greater than 98%, so as to ensure that the established sub-region model can accurately describe the characteristics and morphology of the closed sub-region and finally obtain accurate and reliable evaluation results. Otherwise, if there are deviations or mismatches between the established sub-region model and the closed sub-region, the evaluation results will be distorted or inaccurate. Specifically, when the number of plate classification lines is small and the shape of the plate classification line is a non-linear curve, it is preferred to use the classification line function model to establish the sub-region model to ensure a high matching degree between the established sub-region model and the closed sub-region; when the number of plate classification lines is large or the shapes of the plate classification lines are all straight lines / line segments, it is preferred to use the scatter data fence model to establish the sub-region model, so as to reduce the implementation difficulty while ensuring a high matching degree between the established sub-region model and the closed sub-region. The main steps of establishing the sub-region model by using the classification line function model include: respectively determining the unique mapping relationship of the variable data on each extended classification line on the plate. If the unique mapping relationship of the variable data cannot be determined on the plate classification line, the plate classification line is segmented into multiple sub-classification lines, and the unique mapping relationship of the variable data is determined on the multiple sub-classification lines; selecting multiple anchor points on the extended plate classification line, and encrypting the selection of anchor points at the places where the classification line curve changes violently; determining the accurate coordinates of the multiple anchor points based on the plate coordinate axes; establishing a function model based on the multiple anchor points on each plate classification line, fitting the extended classification line, and forming several classification line function models. The main steps of establishing the sub-region model by using the scatter data fence model include: selecting multiple anchor points on the edge of each closed sub-region, and encrypting the selection of anchor points at the inflection points and the places where the curve changes violently when there are many inflection points or the edge is a curve; determining the accurate coordinates of the multiple anchor points based on the plate coordinate axes; taking the anchor point coordinates on the edge of each non-overlapping closed sub-region as a set respectively, and the polygon model formed by the anchor points and the connecting lines of the anchor points within each set is the scatter data fence model.

[0091] Further, in S6, the mapping relationship between each sub-region model and the evaluation result is determined. In this example, the evaluation result of the sub-region model constructed based on the III-type region is III-type kerogen, and the evaluation result of the sub-region model constructed based on the I-type region is I-type kerogen, etc.

[0092] Further, in S7, based on the mapping relationship between the plate sub-region segmentation model and the evaluation results, the evaluation results of the geological data to be evaluated are determined by the domain-by-domain discrimination method. The specific method includes determining the evaluation results of the geological data to be evaluated by the domain-by-domain discrimination method based on the classification line function model or the scatter data fence model. Among them, determining the evaluation results of the geological data to be evaluated by the domain-by-domain discrimination method based on the classification line function model includes: dividing the plate with the curve of the classification line function model as the boundary; determining the evaluation order of the geological data within each plate sub-region; calculating the numerical value of the geological data on the plate classification line based on the geological data mapping relationship, the plate classification line function model, and the evaluation order of the geological data within the plate sub-region; comparing the numerical value of the geological data on the plate classification line with the numerical value of the geological data to be evaluated, determining the sub-region model to which the geological data to be evaluated belongs, and obtaining the evaluation results of the geological data according to the mapping relationship between the sub-region model and the evaluation results; repeating the above steps until the evaluation results of all geological data are obtained. Determining the evaluation results of the geological data to be evaluated by the domain-by-domain discrimination method based on the scatter data fence model includes: for each geological data, randomly construct a straight line passing through the geological data. If the straight line passes through any anchor point in the scatter data fence model, then randomly construct a straight line passing through the geological data until the constructed straight line does not pass through any anchor point in the scatter data fence model. Denote the equation of the straight line as:

[0093] Ax + By + C = 0

[0094] Taking the data point as an endpoint, extend it in any direction on the straight line to form a ray; calculate the intersection points of the ray and the connection lines of all adjacent anchor points in each scatter data fence model, and count the number of intersection points; extract the scatter data fence models with an odd number of intersection points; obtain the evaluation results corresponding to the extracted scatter data fence models according to the mapping relationship between the sub-region model and the evaluation results, that is, obtain the evaluation results of the geological data; repeat the above steps until the evaluation results of all geological data are obtained.

[0095] Among them, the method for calculating and counting the number of intersection points of the ray and each scatter data fence model includes: sequentially calculating the equations of the straight lines formed by any two adjacent anchor points in the scatter data fence model, denoted as:

[0096] ax + by + c = 0

[0097] Calculating the solution of the system of equations composed of Ax + By + C = 0 and ax + by + c = 0, which is the intersection point coordinates of the two straight lines; checking the position of the intersection point. If the intersection point coordinates are within the ray coordinate range and the intersection point is within the coordinates of the two anchor points of the anchor point connection line, then it is judged that the intersection point is on the anchor point connection line, triggering the intersection point counting, otherwise it is judged that the ray does not intersect with the anchor point connection line. Repeat the above steps until the statistical result of the number of intersection points of the ray and all anchor point connection lines is obtained.

[0098] The following further elaborates on the specific implementation of the present invention according to specific embodiments. The method of this embodiment is applied to the evaluation of organic matter types using the HI-Tmax chart.

[0099] S1 Obtain the experimental analysis data of the core and determine the effective data range of the experimental analysis data;

[0100] Retrieve the pyrolysis experimental analysis data of the shale core of a certain well. In some embodiments, 218 data values are obtained, as shown in Table 1. Each data value includes the well number, well depth, formation information, hydrogen index HI, and the highest pyrolysis peak temperature Tmax. The formation information includes the first member of the Nenjiang Formation, the second member of the Nenjiang Formation, the second and third members of the Yao Formation, etc. Based on the highest pyrolysis peak temperature values of the 218 data values and the industry evaluation standard, define 400°C < Tmax < 500°C as the effective data range of Tmax; based on the hydrogen index values, define 0 mg / g < HI < 1000 mg / g as the effective data range of HI.

[0101] Table 1 Experimental analysis results of Tamx and HI

[0102]

[0103]

[0104]

[0105]

[0106]

[0107] S2 Combine the data characteristics and analysis purposes to select a suitable data evaluation chart;

[0108] Select the HI-Tmax organic matter type chart based on the general three-category and four-division method in the industry in this embodiment to carry out data evaluation (the chart is as shown in Figure 2 ). The solid line in the chart is the classification line, and the dashed line is the vitrinite reflectance Ro reference line.

[0109] S3 Extend the classification line in the chart (the extended classification line is also collectively referred to as the classification line in the following text) so that the classification line can completely cover the effective data range; if the existing chart cannot completely cover the determined effective data range, at the same time, expand the existing chart according to the research results until the chart can completely cover the effective data range;

[0110] To enable the chart classification line to cover all effective data ranges, add the following 4 groups of auxiliary classification points to the chart:

[0111] The first group of auxiliary classification points: (478, 13), (420, 1000);

[0112] The second set of auxiliary classification points: (400, 564.97), (460, 80), (478, 13);

[0113] The third set of auxiliary classification points: (400, 293.79), (478, 13);

[0114] The fourth set of auxiliary classification points: (400, 128.53).

[0115] Extend the plate classification line to the corresponding auxiliary classification points. The plate after extending the plate classification line is as Figure 3 shown.

[0116] The plate in this embodiment can completely cover the determined effective data range, so the existing plate is not extended.

[0117] S4 Based on the extended plate classification line and the plate coordinate axes, divide the plate into several non-overlapping closed sub-regions that can cover all regions of the plate;

[0118] Based on the extended plate classification line and the plate coordinate axes, divide the plate into 4 non-overlapping closed sub-regions that can cover all regions of the plate. The regions of the plate from bottom to top are Region III, Region II2, Region II1, and Region I (including the blank area in the upper right).

[0119] S5 According to each closed sub-region divided from the plate, establish a sub-region model respectively;

[0120] The sub-region model can be established by using the classification line function model or the scatter data fence model. In this embodiment, the number of plate classification lines is small and the shape of the plate classification line is a non-linear curve. Therefore, the classification line function model should be preferentially used to establish the sub-region model to ensure a high degree of coincidence between the established sub-region model and the closed sub-region. The specific operation of establishing the sub-region model by using the classification line function model is as follows:

[0121] 1. Record a number of anchor points on the 4 curves of the HI-Tmax plate with the extended plate classification line (as Figure 4 shown), and the coordinates of the 4 groups of anchor points are;

[0122] The first group of anchor points:

[0123] (420, 1000), (440.1554, 848.87), (452.1, 697.74), (458.16, 177.97), (460.1, 108.76), (463.08, 79.1), (470.08, 46.61), (475.13, 29.66), (478, 13);

[0124] The second group of anchor points:

[0125] (400, 564.97), (409.974, 564.97), (420.08, 549.44), (430.05, 518.36), (440.16, 473.16), (448.06, 398.31), (452.2, 199.15), (455.18, 124.29), (460, 80), (478, 13);

[0126] The 3rd group of anchor points:

[0127] (400, 293.79), (409.97, 293.79), (420.08, 298.02), (430.18, 268.36), (440.16, 210.45), (450.26, 132.77), (455.18, 98.87), (460.23, 63.56), (465.16, 39.548), (470.21, 29.66), (478, 13);

[0128] The 4th group of anchor points:

[0129] (400, 128.53), (410.1, 128.53), (420.21, 138.42), (430.052, 115.82), (440.1554, 84.75), (450.13, 49.44), (460.1, 26.84), (480.1, 11.3), (500, 4).

[0130] 2. Based on the anchor points on the curve, use a function to fit the 4 curves in the figure.

[0131] Define the 4 curves from top to bottom in the plate as the 1st plate classification line, the 2nd plate classification line, the 3rd plate classification line, and the 4th plate classification line (the same below).

[0132] To make the mapping relationship between geological data unique and the fitting effect optimal, select the mapping relationship between geological data on each plate classification line as:

[0133] The 1st plate classification line: HI → Tmax;

[0134] The 2nd plate classification line: HI → Tmax;

[0135] The 3rd plate classification line: Tmax → HI;

[0136] The 4th plate classification line: Tmax → HI;

[0137] Select appropriate functions to fit each plate classification line (or sub-classification line) respectively to obtain the function model of the plate classification line. The function models of each plate classification line from top to bottom in the plate are as follows:

[0138] The 1st plate classification line:

[0139] Tmax 分类线 = 0.0000000004 × HI 分类线 4 - 0.000001 × HI 分类线 3 +

[0140] 0.0008 × HI 分类线 2 - 0.2589 × HI 分类线 + 480.78

[0141] The 2nd plate classification line:

[0142] Tmax 分类线 = - 0.000000002 × HI 分类线 4 + 0.0000006 × HI 分类线 3 +

[0143] 0.0006 × HI 分类线 2 - 0.289 × HI 分类线 + 480.79

[0144] The 3rd plate classification line:

[0145] HI 分类线 = 0.00003 × Tmax 分类线 4 - 0.0538 × Tmax 分类线 3 +

[0146] 34.162 × Tmax 分类线 2 - 9602.8 × Tmax 分类线 4 + 1000000;

[0147] The 4th plate classification line:

[0148] HI 分类线 = - 0.000008 × Tmax 分类线 4 + 0.0157 × Tmax 分类线 3 -

[0149] 10.946×Tmax 分类线 2 +3381.8×Tmax 分类线 -389979

[0150] So far, the sub-region model has been established through the classification line function model.

[0151] To facilitate the understanding of establishing the sub-region model by the scatter data fence model, the method of establishing the sub-region model by the scatter data fence model is briefly described below:

[0152] 1. Select multiple anchor points on the edge of each closed sub-region. The selected anchor points are as Figure 5 shown;

[0153] 2. Determine the accurate coordinates of multiple anchor points based on the chart axes;

[0154] The first group of anchor points (including the blank area I type area in the upper right):

[0155] (400, 564.97), (409.974, 564.97), (420.08, 549.44), (430.05, 518.36), (440.16, 473.16), (448.06, 398.31), (452.2, 199.15), (455.18, 124.29), (460, 80), (478, 13), (500, 4), (500, 1000), (400, 1000).

[0156] The second group of anchor points (II1 type area):

[0157] (400, 564.97), (409.974, 564.97), (420.08, 549.44), (430.05, 518.36), (440.16, 473.16), (448.06, 398.31), (452.2, 199.15), (455.18, 124.29), (460, 80), (478, 13), (470.21, 29.66), (465.16, 39.548), (460.23, 63.56), (455.18, 98.87), (450.26, 132.77), (440.16, 210.45), (430.18, 268.36), (420.08, 298.02), (409.97, 293.79), (400, 293.79).

[0158] The third group of anchor points (II2 type area):

[0159] (400, 293.79), (409.97, 293.79), (420.08, 298.02), (430.18, 268.36), (440.16, 210.45), (450.26, 132.77), (455.18, 98.87), (460.23, 63.56), (465.16, 39.548), (470.21, 29.66), (478, 13), (480.1, 11.3), (460.1, 26.84), (450.13, 49.44), (440.1554, 84.75), (430.052, 115.82), (420.21, 138.42), (410.1, 128.53), (400, 128.53).

[0160] The 4th group of anchor points (Type III region):

[0161] (400, 128.53), (410.1, 128.53), (420.21, 138.42), (430.052, 115.82), (440.1554, 84.75), (450.13, 49.44), (460.1, 26.84), (480.1, 11.3), (500, 4), (500, 0), (400, 0).

[0162] 3. Take the anchor point coordinates on the edge of each non - overlapping closed sub - region as a set respectively. The polygon model formed by the anchor points and the connecting lines of the anchor points within each set is the scatter - data fence model.

[0163] S6 Determine the mapping relationship between each sub - region model and the evaluation result;

[0164] 1. The mapping relationship between the sub - region model established by the classification - line function model and the evaluation result is as follows:

[0165] The area below the 4th plate classification line is defined as the Type III kerogen region, and the kerogen corresponding to the data is defined as Type III kerogen;

[0166] The area between the 3rd plate classification line and the 4th plate classification line is defined as the Type II2 kerogen region, and the kerogen corresponding to the data is defined as Type II2 kerogen;

[0167] The area between the 2nd plate classification line and the 3rd plate classification line is defined as the Type II1 kerogen region, and the kerogen corresponding to the data is defined as Type II1 kerogen;

[0168] Other areas on the plate are defined as the Type I kerogen region, and the kerogen corresponding to the data is defined as Type I kerogen.

[0169] 2. The mapping relationship between the sub-region model established for the scatter data fence model and the evaluation results is as follows:

[0170] The polygonal region enclosed by the first set of anchor points and their connecting lines corresponds to the blank area type I region in the upper right part, and the kerogen corresponding to the data is defined as type I kerogen;

[0171] The polygonal region enclosed by the second set of anchor points and their connecting lines corresponds to the II1 type region, and the kerogen corresponding to the data is defined as type II1 kerogen;

[0172] The polygonal region enclosed by the third set of anchor points and their connecting lines corresponds to the II2 type region, and the kerogen corresponding to the data is defined as type II2 kerogen;

[0173] The polygonal region enclosed by the fourth set of anchor points and their connecting lines corresponds to the III type region, and the kerogen corresponding to the data is defined as type III kerogen.

[0174] S7 determines the evaluation result of the geological data to be evaluated through the domain-by-domain discrimination method based on the mapping relationship between the sub-region model and the evaluation results.

[0175] Determine the evaluation result of the geological data to be evaluated based on the domain-by-domain discrimination method of the classification line function model

[0176] 1. Divide the chart with the curve of the classification line function model as the boundary to form 4 non-overlapping closed sub-regions: the region below the fourth chart classification line, the region between the third and fourth chart classification lines, the region between the second and third chart classification lines, and other regions in the chart.

[0177] 2. Determine the evaluation order of the geological data within each chart sub-region:

[0178] ① If Tmax < 400 or Tmax > 500, it is data outside the effective range and is evaluated as ' / ' (or other custom forms);

[0179] ② If HI >= 564.97, the data point is above curve 2 and is evaluated as type I kerogen;

[0180] ③ If Tmax < 128.53 (the highest point of curve 4), substitute the Tmax value into curve 4 to obtain the HI 分类线 value on the curve. If the actual HI of the data <= HI 分类线 , then the data point is below curve 4 and is evaluated as type III kerogen;

[0181] ④ If 400 <= Tmax <= 478, use Tmax to obtain the HI 分类线 value on curve 3. If the actual HI <= HI 分类线, then this data point is below Curve 3 and is evaluated as Type Ⅱ2 kerogen;

[0182] ⑤ If 13 < HI < 564.97, use HI to obtain the Tmax value on Curve 2. If Tmax 分类线 ≥ Tmax, then this data point falls to the left of Curve 2 and is evaluated as Type Ⅱ1; otherwise, if the data does not fall to the left of Curve 2, it is all evaluated as Type Ⅰ; 分类线 >=Tmax, then this data point falls to the left of Curve 2 and is evaluated as Type Ⅱ1; otherwise, if the data does not fall to the left of Curve 2, it is all evaluated as Type Ⅰ;

[0183] 3. Based on the mapping relationship of geological data, the function model of the classification line on the chart, and the evaluation order of geological data within the sub-region of the chart, calculate the numerical value of geological data on the classification line of the chart; compare the numerical values of geological data on the classification line of the chart with those of the geological data to be evaluated, determine the sub-region model to which the geological data to be evaluated belongs, and obtain the evaluation result of the geological data according to the mapping relationship between the sub-region model and the evaluation result. Use a computer program to batch process all data in sequence according to the above evaluation method to obtain the evaluation result of the geological data (as shown in Table 2). Map the data in this method to the Figure 2 chart shown to obtain Figure 6 . Through manual point-by-point verification, the results obtained by this method are all correct.

[0184] In addition, this method also determines the evaluation result of the geological data to be evaluated based on the domain-by-domain discrimination method of the scatter data fence model. Taking the Type Ⅰ kerogen data shown in Figure 7 as an example:

[0185] 1. For a straight line randomly constructed through geological data, if the straight line passes through any anchor point in the scatter data fence model, then randomly construct another straight line through the geological data until the constructed straight line does not pass through any anchor point in the scatter data fence model. Taking the data point as an endpoint, extend it in any direction on the straight line to form a ray (as shown in Figure 7 ), calculate the intersection points of the ray and all anchor points and the connecting lines of the anchor points in each scatter data fence model, and count the number of intersection points. The results are as follows:

[0186] The number of intersection points of the ray and the polygon area surrounded by the first group of anchor points and their connecting lines is 1;

[0187] The number of intersection points of the ray and the polygon area surrounded by the second group of anchor points and their connecting lines is 2;

[0188] The number of intersection points of the ray and the polygon area surrounded by the second group of anchor points and their connecting lines is 2;

[0189] The number of intersection points of the ray and the polygon area surrounded by the second group of anchor points and their connecting lines is 2;

[0190] 2. Extract the scatter data fence model with an odd number of intersection points as the first group of anchor points and the polygon model formed by them (including the blank area I type area in the upper right).

[0191] 3. According to the mapping relationship between the sub-region model and the evaluation result, the evaluation result corresponding to the extracted scatter data fence model is type I kerogen, that is, the evaluation result of the geological data is type I kerogen.

[0192] Repeat the above steps to obtain the evaluation results of all geological data.

[0193] Table 2 Evaluation results of organic matter types

[0194]

[0195]

[0196]

[0197]

[0198]

[0199] According to the evaluation results obtained by this method, data statistical analysis can be conveniently carried out. The quantitative statistical results of organic matter types are shown in Table 1, where the data format is: number of data points (percentage).

[0200] Table 3 Quantitative statistical results of organic matter types

[0201] Stratigraphic horizon Type Ⅰ <![CDATA[Type Ⅱ1]]> <![CDATA[Type Ⅱ2]]> Type Ⅲ The second member of the Nenjiang Formation 37(95％) 2(5％) / / The first member of the Nenjiang Formation 124(74％) 23(14％) 7(4％) 14(8％) The second and third members of the Yao Formation / 1(9％) 1(9％) 9(82％)

[0202] It should be particularly noted that each step in each embodiment of the above-mentioned geological data evaluation method based on the chart can be mutually crossed, replaced, added, or deleted. Therefore, these reasonable permutation and combination transformations for the geological data evaluation method based on the chart should also fall within the protection scope of the present invention, and the protection scope of the present invention should not be limited to the embodiments.

[0203] Based on the above purpose, the second aspect of the embodiments of the present invention proposes a geological data evaluation device based on the chart. Figure 8 The figure shows a schematic diagram of an embodiment of the geological data evaluation device based on the chart provided by the present invention. As Figure 8 shown, the geological data evaluation device based on the chart in the embodiments of the present invention includes the following modules:

[0204] Data acquisition module 011, configured to acquire the experimental analysis data of the core and determine the effective data range of the experimental analysis data;

[0205] The plate building module 012 is configured to select a suitable data evaluation plate, and make the plate fully cover the effective data range by extending the classification line and expanding the plate method, and divide the plate into several non-overlapping closed sub-regions that can cover all regions of the plate;

[0206] The model building module 013 is configured to respectively build sub-region models according to each closed sub-region divided by the plate, and determine the mapping relationship between each sub-region model and the evaluation result;

[0207] The data evaluation module 014 is configured to determine the evaluation result of the geological data to be evaluated by the domain-by-domain discrimination method based on the mapping relationship between the sub-region model and the evaluation result.

[0208] Finally, it should be noted that those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The program of the geological data evaluation method based on the plate can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. Among them, the storage medium of the program can be a magnetic disk, an optical disc, a read-only memory (ROM), or a random access memory (RAM), etc. The embodiments of the above computer program can achieve the same or similar effects as the corresponding foregoing method embodiments.

[0209] In addition, the method disclosed according to the embodiments of the present invention can also be implemented as a computer program executed by a processor, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the above functions defined in the method disclosed in the embodiments of the present invention are executed.

[0210] In addition, the above method steps and system units can also be implemented by a controller and a computer-readable storage medium for storing a computer program that enables the controller to implement the above steps or unit functions.

[0211] Those skilled in the art will also understand that the various exemplary logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability of hardware and software, a general description has been given of the functions of various illustrative components, blocks, modules, circuits, and steps. Whether this function is implemented as software or as hardware depends on the specific application and the design constraints imposed on the overall system. The functions that those skilled in the art can implement in various ways for each specific application, but this implementation decision should not be construed as causing a departure from the scope of the disclosure of the embodiments of the present invention.

[0212] In one or more exemplary designs, the functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functionality may be stored on or transmitted via a computer-readable medium as one or more instructions or code. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one location to another. The storage media may be any available media that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a general purpose or special purpose computer or a general purpose or special purpose processor. Additionally, any connection is properly termed a computer-readable medium. For example, if software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. As used herein, disk and disc include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk, and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0213] The above are exemplary embodiments disclosed by the present invention. However, it should be noted that various changes and modifications can be made without departing from the scope of the embodiments disclosed by the present invention as defined by the claims. The functions, steps, and / or actions of the method claims according to the disclosed embodiments herein need not be performed in any particular order. In addition, although the elements disclosed by the embodiments of the present invention may be described or claimed in individual form, they may also be understood as plural unless explicitly limited to the singular.

[0214] It should be understood that, as used herein, unless the context clearly supports the contrary, the singular form "a" is also intended to include the plural form. It should also be understood that the "and / or" used herein refers to any and all possible combinations of one or more of the associated listed items.

[0215] The serial numbers of the disclosed embodiments of the present invention above are merely for description and do not represent the superiority or inferiority of the embodiments.

[0216] Those of ordinary skill in the art can understand that all or part of the steps to implement the above embodiments can be completed by hardware, or can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium, and the above-mentioned storage medium can be a read-only memory, a magnetic disk or an optical disc, etc.

[0217] Those of ordinary skill in the art should understand that the discussion of any above embodiment is only exemplary, and is not intended to imply that the scope (including the claims) disclosed by the embodiments of the present invention is limited to these examples; under the idea of the embodiments of the present invention, the technical features in the above embodiments or different embodiments can also be combined, and there are many other variations in different aspects of the embodiments of the present invention as above, and they are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention shall be included in the protection scope of the embodiments of the present invention.

Claims

1. A method for evaluating geological data based on a graphical plate, comprising the following steps: Obtain the experimental analysis data of the core and determine the effective data range of the experimental analysis data; Select appropriate data evaluation charts based on data characteristics and analysis purposes; Extending the classification lines in the plate so that the classification lines can completely cover the valid data range; Based on the extended plate classification lines and plate coordinate axes, the plate is divided into a plurality of closed sub-areas that do not overlap each other and cover all areas of the plate; According to each closed sub-region segmented by the plate, a sub-region model is established respectively; Determining a mapping relationship between each sub-region model and the evaluation result; Based on the mapping relationship between the sub-region model and the evaluation result, the evaluation result of the geological data to be evaluated is determined by a domain-by-domain discrimination method.

2. The method for evaluating geological data based on a graphical plate according to claim 1, wherein Determine the valid data range for experimental analysis data, including: Identify and eliminate invalid data in the experimental analysis data; Obtain the effective data range recommended in relevant evaluation standards and materials; The effective data range is determined comprehensively by combining the relevant evaluation standards and the effective data range recommended in the materials, regional geology and sample characteristics.

3. The method for evaluating geological data based on a graphical plate according to claim 1, wherein Extend the classification lines in the plate so that they fully cover the valid data range, including: Adding auxiliary classification points to multiple classification lines of the plate based on the valid data range, and sequentially extending the multiple classification lines of the plate to the corresponding auxiliary classification points; Repeat the above steps until all classification lines intersect on the plate classification line or on the plate coordinate axis.

4. The method for evaluating geological data based on a graphical plate according to claim 1, wherein According to each closed sub-region segmented by the plate, a sub-region model is established respectively, including: The sub-region model is established using the classified line function model or the scattered data fence model.

5. The method for evaluating geological data based on a graphical plate according to claim 4, wherein The sub-region model is established by using a classification line function model or a scattered data fence model, further comprising: The established sub-region model should be completely consistent with the closed sub-region or the consistency degree should be greater than 98% to ensure that the established sub-region model can accurately describe the characteristics and morphology of the closed sub-region and ultimately obtain accurate and reliable evaluation results; otherwise, if there is a deviation or inconsistency between the established sub-region model and the closed sub-region, the evaluation results will be distorted or inaccurate; When the number of plate classification lines is small and the shape of the plate classification lines is a nonlinear curve, the classification line function model is preferably used to establish the sub-region model to ensure that the established sub-region model has a high degree of consistency with the closed sub-region; When there are a large number of plate classification lines or the shapes of the plate classification lines are all straight lines or line segments, the scattered data fence model is used to establish the sub-region model, so as to ensure that the established sub-region model has a high degree of consistency with the closed sub-region while reducing the difficulty of implementation.

6. The method for evaluating geological data based on a graphical plate according to claim 4, wherein The sub-region model established by using the classification line function model also includes: Determine the unique mapping relationship of the variable data on each extended classification line on the plate; Select multiple anchor points on the extended classification line, and select more anchor points when the classification line curve changes dramatically; Determine the exact coordinates of multiple anchor points based on the coordinate axes of the plate; A function model is established based on multiple anchor points on each plate classification line, and the extended classification lines are fitted to form several classification line function models.

7. The method for evaluating geological data based on a graphical plate according to claim 6, wherein Determine the unique mapping relationship of the variable data on each extended classification line on the plate, including: In response to the inability to determine the unique data mapping relationship of variables on the plate classification line, the plate classification line is divided into multiple sub-classification lines, and the unique data mapping relationship of variables is determined on the multiple sub-classification lines.

8. The method for evaluating geological data based on a graphical plate according to claim 4, wherein Establishing a sub-region model using the scatter data fence model further includes: Selecting multiple anchor points on the edge of each enclosed sub-region. When there are many edge inflection points or the edge is a curve, the anchor points should be densely selected at the inflection points and where the curve trend changes drastically; Determining the accurate coordinates of multiple anchor points based on the plate coordinate axes; Taking the anchor point coordinates on the edge of each non-overlapping enclosed sub-region as a set respectively. The polygon model formed by the anchor points and the connecting lines of the anchor points within each set is the scatter data fence model.

9. The method for evaluating geological data based on a graphic plate according to claim 1, wherein, Based on the mapping relationship between the plate sub-region separation model and the evaluation result, determining the evaluation result of the geological data to be evaluated through the domain-by-domain discrimination method, including: Determining the evaluation result of the geological data to be evaluated through the domain-by-domain discrimination method based on the classification line function model or the scatter data fence model.

10. The method for evaluating geological data based on a graphic plate according to claim 9, wherein, Determining the evaluation result of the geological data to be evaluated through the domain-by-domain discrimination method based on the classification line function model, including: Dividing the plate with the curve of the classification line function model as the boundary; Determining the evaluation order of the geological data within each plate sub-region; Calculating the numerical value of the geological data on the plate classification line based on the geological data mapping relationship, the plate classification line function model, and the evaluation order of the geological data within the plate sub-region; Comparing the numerical values of the geological data on the plate classification line and the geological data to be evaluated, determining the sub-region model to which the geological data to be evaluated belongs, and obtaining the evaluation result of the geological data according to the mapping relationship between the sub-region model and the evaluation result; Repeating the above steps until the evaluation results of all geological data are obtained.

11. The method for evaluating geological data based on a graphic plate according to claim 9, wherein, Determining the evaluation result of the geological data to be evaluated through the domain-by-domain discrimination method based on the scatter data fence model, including: For each geological data, randomly construct a straight line passing through the geological data. If the straight line passes through any anchor point in the scatter data fence model, then randomly construct a straight line passing through the geological data until the constructed straight line does not pass through any anchor point in the scatter data fence model. Denote the equation of this straight line as: Ax + By + C = 0 Taking the data point as an endpoint and extending it in any direction on the straight line as a ray; Calculating the intersection points of the ray and the connecting lines of all adjacent anchor points in each scatter data fence model, and counting the number of intersection points; Extracting the scatter data fence models with an odd number of intersection points; Obtaining the evaluation result corresponding to the extracted scatter data fence model according to the mapping relationship between the sub-region model and the evaluation result, that is, obtaining the evaluation result of the geological data; Repeating the above steps until the evaluation results of all geological data are obtained.

12. The method for evaluating geological data based on a graphic plate according to claim 11, wherein, Calculating the intersection points of the ray and the connecting lines of all adjacent anchor points in each scatter data fence model and counting the number of intersection points, including: Sequentially calculating the equation of the straight line formed by any two adjacent anchor points in the scatter data fence model, denoted as: ax + by + c = 0 Calculating the solution of the system of equations composed of Ax + By + C = 0 and ax + by + c = 0, which is the intersection point coordinates of the two straight lines; Check the position of the intersection point. If the intersection point coordinates are within the ray coordinate range and the intersection point is within the coordinates of the two anchor points on the connecting line of adjacent anchor points, it is determined that the intersection point is on the connecting line of the anchor points, triggering intersection counting; otherwise, it is determined that the ray does not intersect the connecting line of the anchor points. Repeat the above steps until the statistical result of the number of intersection points between the ray and all connecting lines of the anchor points is obtained.

13. An apparatus for evaluating geological data based on a graphic plate, wherein, It includes: A data acquisition module configured to acquire the experimental analysis data of the core and determine the effective data range of the experimental analysis data; A chart establishment module configured to select a suitable data evaluation chart in combination with the data characteristics and analysis purposes, enable the chart to completely cover the effective data range by extending the classification line and expanding the chart method, and divide the chart into several non-overlapping closed sub-regions that can cover all regions of the chart; A model establishment module configured to establish sub-region models respectively according to each closed sub-region divided by the chart and determine the mapping relationship between each sub-region model and the evaluation result; A data evaluation module configured to determine the evaluation result of the geological data to be evaluated through the domain-by-domain discrimination method based on the mapping relationship between the sub-region model and the evaluation result.

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