Logging quantitative prediction method and device for corrosion intensity of carbonate rock

Abstract

According to the quantitative logging prediction method for the corrosion strength of the carbonate rock, the corrosion effect standard sample which is obviously influenced by the corrosion effect is selected as a basis for establishing quantitative evaluation of the corrosion strength, and the corrosion effect standard sample is further verified. And then obtaining a target corrosion strength development index parameter capable of reflecting the corrosion strength, and depicting the corrosion strength of the pore type bioclastic limestone reservoir. According to the evaluation method, basic geological data are fully combined, the quantitative evaluation index of the corrosion strength is constructed according to the target corrosion strength development index parameters, and evaluation on the development scale difference of the pore type bioclastic limestone reservoir of the target interval is more in line with the actual condition of an oil field. According to the method, a specific quantitative method can be provided for depicting the corrosion strength of the existing pore type bioclastic limestone reservoir, the deficiency of diagenesis transformation between the carbonate rock facies and the reservoir is made up, the corrosion strength of the carbonate rock can be accurately described, and a foundation is laid for deterministic depiction of a reservoir unit.

Description

Technical Field

[0001] The present application relates to the technical field of geological exploration and oil and gas exploration, and in particular to a well logging quantitative prediction method and device for carbonate rock dissolution intensity. Background Art

[0002] Carbonate rock is the main reservoir rock type of carbonate oil reservoirs. It is developed on a large scale in some areas and is the main business area of ​​current oil and gas exploration and development. Unlike clastic rocks, carbonate rocks are easily affected by diagenesis, resulting in complex and irregular reservoir porosity and permeability relationships. The distribution range of physical properties of the same lithofacies may be large, or the distribution of physical properties of different lithofacies may overlap.

[0003] At present, the research on carbonate diagenesis is mainly based on qualitative description. Among the many carbonate diagenesis, dissolution, as the diagenesis with the largest impact range and degree, plays an important role in reservoir transformation.

[0004] Therefore, how to accurately describe the dissolution intensity of carbonate rocks has become a technical problem that urgently needs to be solved in this field. Summary of the invention

[0005] The embodiment of the present application provides a well logging quantitative prediction method for carbonate rock dissolution intensity to solve the problem of how to accurately describe the dissolution intensity of carbonate rocks in the prior art.

[0006] The present application provides a method for quantitatively predicting carbonate rock dissolution intensity by well logging, comprising:

[0007] Obtaining a dissolution standard sample associated with a target layer segment and intensity grade data corresponding to the dissolution standard sample;

[0008] Obtaining a measurement intersection line for the target layer segment according to the dissolution standard sample, and determining whether the measurement intersection line deviates from a preset limestone lithology line;

[0009] If there is a deviation, the obtained dissolution intensity development index parameter is subjected to correlation screening according to the dissolution standard sample to obtain the target dissolution intensity development index parameter;

[0010] A quantitative evaluation index of dissolution intensity is constructed according to the target dissolution intensity development index parameter, and a quantitative prediction is made on the dissolution intensity of the target layer segment to be measured according to the quantitative evaluation index of dissolution intensity.

[0011] Optionally, obtaining a dissolution standard sample associated with a target layer segment and strength grade data corresponding to the dissolution standard sample includes:

[0012] Determine the lithofacies division strategy and porosity and permeability intersection data for the target layer segment according to the obtained basic geological data; wherein the lithofacies division strategy is a basic lithofacies division strategy obtained by core description based on sedimentary characteristics;

[0013] Obtaining candidate samples of dissolution according to the lithofacies division strategy and the pore-permeability intersection data;

[0014] A dissolution standard sample and intensity grade data corresponding to the dissolution standard sample are selected from the dissolution candidate samples according to the obtained multi-dimensional characteristic information of the target layer segment.

[0015] Optionally, determining the lithofacies division strategy and porosity and permeability intersection data for the target layer segment according to the obtained basic geological data includes:

[0016] Obtaining single well lithofacies research data and core well basic data from the basic geological data;

[0017] Acquire the lithofacies division strategy and porosity and permeability data samples of the target layer segment according to the single well lithofacies research data;

[0018] According to the core well basic data, the porosity and permeability data samples of the target layer section are intersected to obtain porosity and permeability intersection data.

[0019] Optionally, obtaining the candidate sample of dissolution according to the lithofacies division strategy and the pore-permeability intersection data includes:

[0020] Analyzing the porosity and permeability intersection data of the target layer segment according to the lithofacies division strategy to obtain a first result that the physical properties of the target layer segment cannot be distinguished;

[0021] Determining the influencing factor of the target layer segment as a dissolution factor according to the porosity and permeability intersection data of the target layer segment and the basic geological data;

[0022] According to the first result and the dissolution factor, data samples with complex and chaotic porosity and permeability intersections are removed from the porosity and permeability intersection data of the target layer segment to obtain dissolution candidate samples.

[0023] Optionally, the multi-dimensional characteristic information of the target layer segment includes at least: diagenetic phenomenon characteristic information, reservoir-permeability space type characteristic information and reservoir-permeability space development and distribution characteristic information;

[0024] Correspondingly, the step of selecting a dissolution standard sample from the dissolution candidate samples according to the obtained multi-dimensional characteristic information of the target layer segment includes:

[0025] A dissolution standard sample is selected from the dissolution candidate samples according to the diagenetic phenomenon characteristic information, the reservoir-seepage space type characteristic information and the reservoir-seepage space development and distribution characteristic information.

[0026] Optionally, the strength level data of the standard sample includes at least an underdeveloped strength level, a weakly developed strength level, a medium developed strength level and a developed strength level.

[0027] Optionally, obtaining a measurement intersection line for the target layer segment according to the dissolution standard sample, and judging whether the measurement intersection line deviates from a preset limestone lithology line, comprises:

[0028] Obtaining a standard sample logging value according to the dissolution standard sample;

[0029] According to the standard sample logging values, a first intersection line of neutron porosity logging values ​​and density logging values ​​and a second intersection line of sonic time difference logging values ​​and density logging values ​​are generated;

[0030] Comparing the first intersection line and the second intersection line with the preset limestone lithology line respectively, and determining whether the first intersection line and the second intersection line deviate from the preset limestone lithology line respectively;

[0031] If there is a deviation, it is determined that the target layer segment has dissolution characteristics consistent with the dissolution effect.

[0032] Optionally, the step of performing correlation screening on the obtained dissolution intensity development index parameter according to the dissolution standard sample to obtain the target dissolution intensity development index parameter includes:

[0033] obtaining candidate dissolution intensity development index parameters associated with the dissolution standard sample;

[0034] According to a preset analysis strategy, the candidate dissolution intensity development index parameters are screened to obtain target dissolution intensity development index parameters.

[0035] Optionally, the target dissolution intensity development index parameter includes at least: density logging value, neutron porosity logging value, deep resistivity logging value, microsphere resistivity logging value, and sonic time difference logging value.

[0036] Optionally, constructing a quantitative evaluation index of dissolution intensity according to the target dissolution intensity development index parameter includes:

[0037] According to the target dissolution intensity development index parameter, a multivariate linear regression strategy is adopted to construct a calculation formula for the dissolution intensity development index;

[0038] Obtaining a calculation result for the dissolution intensity development index according to the calculation formula of the dissolution intensity development index, and comparing the calculation result with the intensity grade data of the associated dissolution standard sample;

[0039] If the comparison results are consistent, the calculation formula of the dissolution intensity development index is determined as a quantitative evaluation index of the dissolution intensity.

[0040] Optionally, also include:

[0041] According to the calculation formula of the dissolution intensity development index, a dissolution intensity quantitative evaluation curve is obtained;

[0042] According to the strength grade data of the standard sample, a standard reference curve for dissolution intensity classification is obtained;

[0043] Comparing the quantitative evaluation curve of dissolution intensity with the standard reference curve of dissolution intensity classification;

[0044] If the comparison results are consistent, the quantitative evaluation curve of dissolution intensity is determined as the quantitative evaluation index of dissolution intensity.

[0045] Technical effects and advantages of this application:

[0046] The present application provides a method for quantitative prediction of carbonate rock dissolution intensity by well logging. The method for quantitative prediction of carbonate rock dissolution intensity provided by the present application takes into account the sedimentary background and diagenesis at the same time. On the basis of basic lithofacies division, standard samples of dissolution that are more significantly affected by dissolution are selected as the basis for establishing quantitative evaluation of dissolution intensity, and the standard samples of dissolution are further verified. Then, the principal component analysis method and the multivariate linear regression method are used to obtain the target dissolution intensity development index parameter that can reflect the dissolution intensity, so as to achieve the characterization of the dissolution intensity of porous bioclastic limestone reservoirs. This evaluation method fully combines the basic geological data, especially constructs a quantitative evaluation index of dissolution intensity based on the target dissolution intensity development index parameter. The evaluation of the scale differences of the development of porous bioclastic limestone reservoirs in the target layer is more in line with the actual oil field, and this method is more in line with the production needs of the oil field site. The research results can provide a specific quantitative method for the characterization of the dissolution intensity of porous bioclastic limestone reservoirs, make up for the lack of diagenetic transformation between carbonate rock facies and reservoirs, accurately describe the dissolution intensity of carbonate rocks, and lay the foundation for the deterministic characterization of reservoir units. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flow chart of the well logging quantitative prediction method of carbonate rock dissolution intensity provided in the first embodiment of the present application;

[0048] Figure 2It is a porosity and permeability intersection diagram of the basic lithofacies division scheme provided in the first embodiment of the present application.

[0049] Figure 3 This is a schematic diagram of the thin section photos corresponding to the classification of dissolution intensity levels in the first embodiment of the present application.

[0050] Figure 4 It is the first intersection line diagram of neutron porosity logging values ​​and density logging values ​​provided in the first embodiment of the present application.

[0051] Figure 5 It is a second intersection line diagram of the acoustic time difference logging value and the density logging value provided in the first embodiment of the present application.

[0052] Figure 6 This is a schematic diagram of the principal component analysis provided in the first embodiment of the present application.

[0053] Figure 7 It is a schematic diagram of the multivariate linear regression analysis provided in the first embodiment of the present application.

[0054] Figure 8 It is a single-well bar graph of the dissolution intensity index of a test well provided in the first embodiment of the present application.

[0055] Fig. 9 It is a schematic diagram of a well logging quantitative prediction device for carbonate rock dissolution intensity provided in the second embodiment of the present application.

[0056] Fig.10 This is a schematic diagram of an electronic device provided in the third embodiment of the present application. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0058] At present, the research on carbonate diagenesis is mainly based on qualitative description. Among the many diagenesis of carbonate rocks, dissolution, as the diagenesis with the largest impact range and degree, plays an important role in reservoir transformation. In this regard, the embodiment of the present application provides a method to solve the technical problem of how to accurately describe the dissolution intensity of carbonate rocks in the prior art.

[0059] The present application is described in detail below through multiple embodiments and drawings.

[0060] First embodiment

[0061] The first embodiment of the present application provides a method for quantitatively predicting carbonate rock dissolution intensity by logging. Figure 1 The logging quantitative prediction method for carbonate rock dissolution intensity is explained in detail.

[0062] Step S101: obtaining a dissolution standard sample associated with a target layer segment and intensity grade data corresponding to the dissolution standard sample.

[0063] Step S102: obtaining a measurement intersection line for the target layer segment according to the dissolution standard sample, and determining whether the measurement intersection line deviates from a preset limestone lithology line.

[0064] Step S103: If there is a deviation, the obtained dissolution intensity development index parameter is subjected to correlation screening according to the dissolution standard sample to obtain the target dissolution intensity development index parameter.

[0065] Step S104: constructing a quantitative evaluation index of dissolution intensity according to the target dissolution intensity development index parameter, and quantitatively predicting the dissolution intensity of the target layer segment to be measured according to the quantitative evaluation index of dissolution intensity.

[0066] In one embodiment, step S101 of obtaining a standard sample of dissolution associated with a target layer segment and strength grade data corresponding to the standard sample of dissolution includes the following contents:

[0067] Specifically, first, determine the lithofacies division strategy and porosity and permeability intersection data for the target layer segment based on the obtained basic geological data. Among them, in this step, the basic geological data are pre-measured geological data, and the lithofacies division strategy is a basic lithofacies division strategy obtained by core description based on sedimentary characteristics. This step specifically includes: obtaining single-well lithofacies research data and coring well basic data in the basic geological data, and obtaining the lithofacies division strategy and porosity and permeability data samples of the target layer segment based on the single-well lithofacies research data, wherein the single-well lithofacies research data at least includes coarse-grained limestone phase data, fine-grained limestone data, particle-dominated mud-grained limestone phase data, lime mud-dominated mud-grained limestone phase data, granular mud limestone phase data and mud-crystal limestone phase data, and obtain the corresponding lithofacies division strategy based on different single-well lithofacies research data. Then, based on the coring well basic data, the porosity and permeability data samples of the target layer segment are intersected by porosity and permeability to obtain porosity and permeability intersection data. See. Figure 2 , Figure 2 It is a porosity and permeability intersection diagram of the basic lithofacies division scheme provided in the embodiment of the present application.

[0068] After obtaining the lithofacies division strategy and the porosity and permeability intersection data for the target layer, the candidate samples of dissolution are obtained according to the lithofacies division strategy and the porosity and permeability intersection data. Specifically, the porosity and permeability intersection data of the target layer are analyzed according to the lithofacies division strategy to obtain a first result that the physical properties of the target layer cannot be distinguished, or to obtain a second result that the physical properties of the target layer can be distinguished, for example, by Figure 2 It can be seen that the granular limestone and micrite limestone in this area have good zoning, and the second result of physical property differentiation can be directly used for strength grade classification. However, the porosity and permeability distribution of the mudstone and granular marl in this area are more cross-sectional and messy. Then, according to the porosity and permeability intersection data of the target layer and the basic geological data, the influencing factor of the target layer is determined to be the dissolution factor, and the data samples with complex and chaotic porosity and permeability intersections are eliminated from the porosity and permeability intersection data of the target layer according to the first result and the dissolution factor to obtain the candidate samples of dissolution.

[0069] After obtaining the candidate samples of dissolution, a standard sample of dissolution is selected from the candidate samples of dissolution according to the obtained multi-dimensional characteristic information of the target layer segment, as well as the intensity grade data corresponding to the standard sample of dissolution. Specifically, in one embodiment, the multi-dimensional characteristic information of the target layer segment includes at least: diagenetic phenomenon characteristic information, reservoir-seepage space type characteristic information, and reservoir-seepage space development and distribution characteristic information. Among them, the diagenetic phenomenon characteristic information is used to determine that the influencing factor of the target layer segment is a dissolution factor, and the reservoir-seepage space type characteristic information and the reservoir-seepage space development and distribution characteristic information include at least: pore type characteristic information, secondary pore development degree characteristic information, and secondary pore proportion characteristic information.

[0070] Correspondingly, selecting a dissolution standard sample from the dissolution candidate samples according to the obtained multi-dimensional characteristic information of the target layer segment includes: selecting a dissolution standard sample from the dissolution candidate samples according to the characteristic information of the diagenetic phenomenon, the characteristic information of the reservoir-seepage space type, and the characteristic information of the reservoir-seepage space development and distribution. In one embodiment, as shown in Table 1 and Figure 3 As shown, Figure 3 Schematic diagram of thin-section photos corresponding to the classification of dissolution intensity levels in the embodiment of the present application. According to the dissolution intensity, the degree of development of secondary pores is controlled, and a dissolution intensity classification standard can be established. According to the degree of development, the dissolution intensity can be divided from strong to weak into undeveloped intensity level, weakly developed intensity level, medium developed intensity level and developed intensity level. At the same time, the characteristics of different levels of dissolution intensity are determined. In addition, the intensity levels of the above four levels are assigned, that is, the undeveloped intensity level is set to 1, the weakly developed intensity level is set to 2, the medium developed intensity level is set to 3 and the developed intensity level is set to 4.

[0071] Table 1

[0072]

[0073] Furthermore, in one embodiment, a standard reference curve for dissolution intensity classification is obtained based on the strength grade data of the standard sample, and the standard reference curve for dissolution intensity classification is used for subsequent verification of the accuracy of the dissolution intensity value obtained by well logging calculation.

[0074] In one embodiment, step S102 obtains a measurement intersection line for a target layer segment according to a standard sample of dissolution, and determines whether the measurement intersection line deviates from a preset limestone lithology line, specifically including the following contents:

[0075] Specifically, first, the standard sample logging value is obtained according to the standard sample of dissolution, wherein the standard sample logging value is the logging value of the standard sample of dissolution. Then, according to the standard sample logging value, the first intersection line of the neutron porosity logging value and the density logging value and the second intersection line of the acoustic time difference logging value and the density logging value are generated. Among them, the neutron porosity logging value and the acoustic time difference logging value will increase with the decrease of the density logging value, and show a good linear relationship. After the dissolution section of the target layer is dissolved, the porosity will increase. For the same density logging value, the corresponding neutron porosity value and acoustic time difference logging value are higher. In other words, after dissolution, the dissolution section is more inclined to the direction with good physical property distribution in the neutron porosity logging value-density logging value intersection diagram and the acoustic time difference logging-density logging value intersection diagram. Finally, the first intersection line is compared with the preset limestone lithology line, and the second intersection line is compared with the preset limestone lithology line, and it is determined whether the first intersection line and the second intersection line deviate from the preset limestone lithology line. Figure 4 and Figure 5 As shown, Figure 4 This is a first intersection line graph of neutron porosity logging values ​​and density logging values ​​provided in an embodiment of the present application. Figure 5 The second intersection line diagram of the acoustic time difference logging value and the density logging value provided in the embodiment of the present application. Figure 4 and Figure 5 It can be seen that the neutron, density, and sonic logging curves of the dissolution section are shifted in the direction of better physical properties, especially the neutron-density intersection diagram, which obviously deviates from the limestone lithology line, which is in line with the general law of reservoir transformation by the dissolution section. That is, if the measured intersection line deviates from the preset limestone lithology line, it is determined that the target layer section has the dissolution characteristics consistent with the dissolution effect.

[0076] After determining that the target layer segment has dissolution characteristics consistent with dissolution, in one example, step S103 performs correlation screening on the obtained dissolution intensity development index parameters according to the dissolution standard sample to obtain the target dissolution intensity development index parameters, which specifically include the following contents: Specifically, first, obtain candidate dissolution intensity development index parameters associated with the dissolution standard sample, wherein, in one embodiment, the candidate dissolution intensity development index parameters at least include density logging values, neutron porosity logging values, deep resistivity logging values, microsphere resistivity logging values, and sonic time difference logging values, and natural gamma logging values. Then, according to the preset analysis strategy, the candidate dissolution intensity development index parameters are screened to obtain the target dissolution intensity development index parameters. In one embodiment, the preset analysis strategy is the principal component analysis method, and the target dissolution intensity development index parameters at least include density logging values, neutron porosity logging values, deep resistivity logging values, microsphere resistivity logging values, and sonic time difference logging values. See. Figure 6 and Table 2 below, Figure 6 Schematic diagram of principal component analysis provided in the embodiment of the present application. Table 2 is a diagram of principal component analysis correlation coefficients provided in the embodiment of the present application.

[0077] Table 2

[0078]

[0079] After obtaining the target dissolution intensity development index parameter, a quantitative evaluation index of dissolution intensity is constructed according to the target dissolution intensity development index parameter. In one example, step S103 constructs a quantitative evaluation index of dissolution intensity according to the target dissolution intensity development index parameter, including the following contents:

[0080] Specifically, first, according to the target dissolution intensity development index parameter, a multivariate linear regression strategy is used to construct a calculation formula for the dissolution intensity development index. In one example, Figure 7 It is a schematic diagram of the multivariate linear regression analysis provided in the embodiment of the present application. After linear regression, the calculation formula of the dissolution intensity development index is:

[0081]

[0082] Among them, LOG(K_CORR) represents the dissolution intensity development index; DEN represents the density logging value, CNL represents the neutron porosity logging value, LLD represents the deep resistivity logging value, MSFL represents the microsphere resistivity logging value, and AC represents the acoustic time difference logging value.

[0083] Then, the calculation result of the dissolution intensity development index is obtained according to the calculation formula of the dissolution intensity development index, and the calculation result is compared with the intensity grade data of the associated dissolution standard sample. If the comparison result is consistent, the calculation formula of the dissolution intensity development index is determined as a quantitative evaluation index of the dissolution intensity.

[0084] In one embodiment, the method further includes: obtaining a dissolution intensity quantitative evaluation curve according to a calculation formula for the dissolution intensity development index, obtaining a dissolution intensity classification standard reference curve according to the strength grade data of the standard sample, comparing the dissolution intensity quantitative evaluation curve with the dissolution intensity classification standard reference curve, and if the comparison results are consistent, determining the dissolution intensity quantitative evaluation curve as a quantitative evaluation index of dissolution intensity. Figure 8 , Figure 8 This is a single well bar graph of the dissolution intensity index of a test well provided in an embodiment of the present application. After the dissolution intensity dissolution index is divided according to the range, it is compared with the dissolution intensity, and it is found that there is a good matching relationship between the two, so that the dissolution intensity logging curve can be promoted within the oil field.

[0085] After constructing a quantitative evaluation index of dissolution intensity according to the target dissolution intensity development index parameter, the dissolution intensity of the target layer segment to be measured can be quantitatively predicted according to the quantitative evaluation index of dissolution intensity.

[0086] The logging quantitative prediction method for carbonate rock dissolution intensity provided in this application takes into account the sedimentary background and diagenesis at the same time. On the basis of the basic lithofacies division, the standard dissolution samples that are more significantly affected by dissolution are selected as the basis for establishing the quantitative evaluation of dissolution intensity, and the standard dissolution samples are further verified. Then, the principal component analysis method and the multivariate linear regression method are used to obtain the target dissolution intensity development index parameter that can reflect the dissolution intensity, so as to realize the characterization of the dissolution intensity of the porous bioclastic limestone reservoir. This evaluation method fully combines the basic geological data, especially constructs the quantitative evaluation index of dissolution intensity according to the target dissolution intensity development index parameter, and the evaluation of the development scale difference of the porous bioclastic limestone reservoir in the target layer is more in line with the actual oil field, and this method is more in line with the production needs of the oil field site. The research results can provide a specific quantitative method for the characterization of the dissolution intensity of the porous bioclastic limestone reservoir, make up for the lack of diagenetic transformation between carbonate rock lithofacies and reservoirs, accurately describe the dissolution intensity of carbonate rocks, and lay the foundation for the deterministic characterization of reservoir units.

[0087] Second embodiment

[0088] In the above-mentioned first embodiment, a well logging quantitative prediction method for carbonate rock dissolution intensity is provided. Correspondingly, the third embodiment of the present application provides a well logging quantitative prediction device for carbonate rock dissolution intensity. Since the device embodiment is basically similar to the first embodiment of the method, the description is relatively simple. For relevant parts, please refer to the partial description of the method embodiment. The device embodiment described below is only illustrative.

[0089] Please refer to Fig. 9 , which is a schematic diagram of a well logging quantitative prediction device for carbonate rock dissolution intensity provided in the second embodiment of the present application.

[0090] The well logging quantitative prediction device for carbonate rock dissolution intensity includes: a dissolution standard sample acquisition unit 901, which is used to obtain a dissolution standard sample associated with a target layer segment and strength grade data corresponding to the dissolution standard sample; a measurement intersection linear processing unit 902, which is used to obtain a measurement intersection line for the target layer segment according to the dissolution standard sample, and determine whether the measurement intersection line deviates from a preset limestone lithology line; a target dissolution intensity development index parameter acquisition unit 903, which is used to perform correlation screening on the obtained dissolution intensity development index parameter according to the dissolution standard sample if there is a deviation, so as to obtain the target dissolution intensity development index parameter; a quantitative evaluation index construction unit 904, which is used to construct a quantitative evaluation index of dissolution intensity according to the target dissolution intensity development index parameter, and quantitatively predict the dissolution intensity of the target layer segment to be measured according to the quantitative evaluation index of dissolution intensity.

[0091] Optionally, the dissolution standard sample obtaining unit includes:

[0092] A data processing unit, used to determine the lithofacies division strategy and porosity and permeability intersection data for the target layer segment according to the obtained basic geological data; wherein the lithofacies division strategy is a basic lithofacies division strategy obtained by core description based on sedimentary characteristics;

[0093] A dissolution candidate sample acquisition unit, used for acquiring dissolution candidate samples according to the lithofacies division strategy and the pore-permeability intersection data;

[0094] The dissolution standard sample selection unit is used to select a dissolution standard sample and intensity grade data corresponding to the dissolution standard sample from the dissolution candidate samples according to the obtained multi-dimensional characteristic information of the target layer segment.

[0095] Optionally, the data processing unit includes:

[0096] The first data processing subunit is used to obtain single well lithofacies research data and core well basic data in the basic geological data;

[0097] A second data processing subunit is used to obtain a lithofacies division strategy and porosity and permeability data samples of the target layer segment according to the single well lithofacies research data;

[0098] The third data processing subunit is used to perform porosity and permeability intersection on the porosity and permeability data samples of the target layer segment according to the core well basic data to obtain porosity and permeability intersection data.

[0099] Optionally, the dissolution candidate sample acquisition unit includes:

[0100] A first result obtaining unit is used to analyze the porosity and permeability intersection data of the target layer segment according to the lithofacies division strategy to obtain a first result that the physical properties of the target layer segment cannot be distinguished;

[0101] a dissolution factor determination unit, for determining the influencing factor of the target layer segment as a dissolution factor according to the porosity and permeability intersection data of the target layer segment and the basic geological data;

[0102] The data elimination unit is used to eliminate data samples with complex and chaotic porosity and permeability intersection from the porosity and permeability intersection data of the target layer segment according to the first result and the dissolution factor, so as to obtain candidate samples of dissolution.

[0103] Optionally, the multi-dimensional characteristic information of the target layer segment includes at least: diagenetic phenomenon characteristic information, reservoir-permeability space type characteristic information and reservoir-permeability space development and distribution characteristic information;

[0104] Correspondingly, the dissolution standard sample selection unit is used to select a dissolution standard sample from the dissolution candidate samples according to the diagenetic phenomenon characteristic information, the reservoir-seepage space type characteristic information and the reservoir-seepage space development and distribution characteristic information.

[0105] Optionally, the strength level data of the standard sample includes at least an underdeveloped strength level, a weakly developed strength level, a medium developed strength level and a developed strength level.

[0106] Optionally, the dissolution standard sample selection unit includes:

[0107] A standard sample logging value obtaining unit, used for obtaining a standard sample logging value according to the dissolution standard sample;

[0108] An intersection line generating unit is used to generate a first intersection line of neutron porosity logging values ​​and density logging values ​​and a second intersection line of sonic time difference logging values ​​and density logging values ​​according to the standard sample logging values;

[0109] a judgment unit, configured to compare the first intersection line and the second intersection line with the preset limestone lithology line respectively, and judge whether the first intersection line and the second intersection line deviate from the preset limestone lithology line respectively;

[0110] The determination unit is used to determine that if there is a deviation, the target layer segment has dissolution characteristics consistent with the dissolution effect.

[0111] Optionally, the target dissolution intensity development index parameter obtaining unit includes:

[0112] A candidate dissolution intensity development index parameter obtaining unit, used to obtain a candidate dissolution intensity development index parameter associated with the dissolution standard sample;

[0113] The target dissolution intensity development index parameter screening unit is used to screen the candidate dissolution intensity development index parameters according to a preset analysis strategy to obtain the target dissolution intensity development index parameters.

[0114] Optionally, the target dissolution intensity development index parameter includes at least: density logging value, neutron porosity logging value, deep resistivity, microsphere resistivity, and sonic time difference logging value.

[0115] Optionally, the quantitative evaluation index construction unit includes:

[0116] A dissolution intensity development index calculation formula construction unit is used to construct a dissolution intensity development index calculation formula according to the target dissolution intensity development index parameter by adopting a multivariate linear regression strategy;

[0117] A first comparison unit is used to obtain a calculation result for the dissolution intensity development index according to the calculation formula of the dissolution intensity development index, and compare the calculation result with the intensity grade data of the associated dissolution standard sample;

[0118] The quantitative evaluation index determination unit is used to determine the calculation formula of the dissolution intensity development index as the quantitative evaluation index of the dissolution intensity if the comparison results are consistent.

[0119] Optionally, the quantitative evaluation index construction unit further includes:

[0120] A dissolution intensity quantitative evaluation curve obtaining unit, used to obtain a dissolution intensity quantitative evaluation curve according to the dissolution intensity development index calculation formula;

[0121] A unit for obtaining a standard reference curve for dissolution intensity classification, used for obtaining a standard reference curve for dissolution intensity classification according to the intensity grade data of the standard sample;

[0122] A second comparison unit is used to compare the dissolution intensity quantitative evaluation curve with the dissolution intensity classification standard reference curve;

[0123] The quantitative evaluation index determination unit is used to determine the quantitative evaluation curve of the dissolution intensity as the quantitative evaluation index of the dissolution intensity if the comparison results are consistent.

[0124] Third embodiment

[0125] Corresponding to the above method embodiment of the present application, the third embodiment of the present application further provides an electronic device. Fig.10 As shown, Fig.10 This is a schematic diagram of an electronic device provided in the third embodiment of the present application. The electronic device includes: at least one processor 1001, at least one communication interface 1002, at least one memory 1003 and at least one communication bus 1004; optionally, the communication interface 1002 can be an interface of a communication module, such as an interface of a GSM module; the processor 1001 may be a processor CPU, or an application specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application. The memory 1003 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. Among them, the memory 1003 stores a program, and the processor 1001 calls the program stored in the memory 1003 to execute the method provided in the above embodiment of the present application.

[0126] Fourth embodiment

[0127] Corresponding to the above method of the present application, the fourth embodiment of the present application further provides a computer storage medium. The computer storage medium stores a computer program, which is executed by a processor to execute the method provided in the above embodiment of the present application.

[0128] Although the present application is disclosed as above in the form of a preferred embodiment, it is not intended to limit the present application. Any technical personnel in this field may make possible changes and modifications without departing from the spirit and scope of the present application. Therefore, the scope of protection of the present application shall be based on the scope defined by the claims of the present application.

[0129] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0130] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0131] 1. Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include non-transitory media such as modulated data signals and carrier waves.

[0132] 2. Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0133] It should be noted that the embodiments of the present application may involve the use of user data. In actual applications, user-specific personal data can be used in the scheme described herein within the scope permitted by applicable laws and regulations, subject to the requirements of applicable laws and regulations of the country where the user is located (for example, with the user's explicit consent, effective notification to the user, etc.).

[0134] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

Claims

1. A well logging quantitative prediction method for carbonate rock dissolution intensity, characterized in that: include: Obtaining a dissolution standard sample associated with a target layer segment and intensity grade data corresponding to the dissolution standard sample; Obtaining a measurement intersection line for the target layer segment according to the dissolution standard sample, and determining whether the measurement intersection line deviates from a preset limestone lithology line; If there is a deviation, the obtained dissolution intensity development index parameter is subjected to correlation screening according to the dissolution standard sample to obtain the target dissolution intensity development index parameter; A quantitative evaluation index of dissolution intensity is constructed according to the target dissolution intensity development index parameter, and a quantitative prediction is made on the dissolution intensity of the target layer segment to be measured according to the quantitative evaluation index of dissolution intensity.

2. The method for quantitative prediction of carbonate rock dissolution intensity by well logging according to claim 1, characterized in that: Obtaining a dissolution standard sample associated with a target layer segment and intensity grade data corresponding to the dissolution standard sample, including: Determine the lithofacies division strategy and porosity and permeability intersection data for the target layer segment according to the obtained basic geological data; wherein the lithofacies division strategy is a basic lithofacies division strategy obtained by core description based on sedimentary characteristics; Obtaining candidate samples of dissolution according to the lithofacies division strategy and the pore-permeability intersection data; A dissolution standard sample and intensity grade data corresponding to the dissolution standard sample are selected from the dissolution candidate samples according to the obtained multi-dimensional characteristic information of the target layer segment.

3. The method for quantitative prediction of carbonate rock dissolution intensity by well logging according to claim 2, characterized in that: The step of determining the lithofacies division strategy and porosity and permeability intersection data for the target layer segment based on the obtained basic geological data includes: Obtaining single well lithofacies research data and core well basic data from the basic geological data; Acquire the lithofacies division strategy and porosity and permeability data samples of the target layer segment according to the single well lithofacies research data; According to the core well basic data, the porosity and permeability data samples of the target layer section are intersected to obtain porosity and permeability intersection data.

4. The method for quantitative prediction of carbonate rock dissolution intensity by well logging according to claim 2, characterized in that: The step of obtaining a candidate sample for dissolution according to the lithofacies division strategy and the pore-permeability intersection data includes: Analyzing the porosity and permeability intersection data of the target layer segment according to the lithofacies division strategy to obtain a first result that the physical properties of the target layer segment cannot be distinguished; Determining the influencing factor of the target layer segment as a dissolution factor according to the porosity and permeability intersection data of the target layer segment and the basic geological data; According to the first result and the dissolution factor, data samples with complex and chaotic porosity and permeability intersections are removed from the porosity and permeability intersection data of the target layer segment to obtain dissolution candidate samples.

5. The method for quantitative prediction of carbonate rock dissolution intensity by well logging according to claim 2, characterized in that: The multi-dimensional characteristic information of the target layer segment at least includes: diagenetic phenomenon characteristic information, reservoir-seepage space type characteristic information and reservoir-seepage space development and distribution characteristic information; Correspondingly, the step of selecting a dissolution standard sample from the dissolution candidate samples according to the obtained multi-dimensional characteristic information of the target layer segment includes: A dissolution standard sample is selected from the dissolution candidate samples according to the diagenetic phenomenon characteristic information, the reservoir-seepage space type characteristic information and the reservoir-seepage space development and distribution characteristic information.

6. The method for quantitative prediction of carbonate rock dissolution intensity by well logging according to claim 1, characterized in that: The strength level data of the standard sample at least includes an underdeveloped strength level, a weakly developed strength level, a medium developed strength level and a developed strength level.

7. The method for quantitative prediction of carbonate rock dissolution intensity by well logging according to claim 1, characterized in that: The step of obtaining a measurement intersection line for the target layer segment according to the dissolution standard sample and determining whether the measurement intersection line deviates from a preset limestone lithology line includes: Obtaining a standard sample logging value according to the dissolution standard sample; According to the standard sample logging values, a first intersection line of neutron porosity logging values ​​and density logging values ​​and a second intersection line of sonic time difference logging values ​​and density logging values ​​are generated; Comparing the first intersection line and the second intersection line with the preset limestone lithology line respectively, and determining whether the first intersection line and the second intersection line deviate from the preset limestone lithology line respectively; If there is a deviation, it is determined that the target layer segment has dissolution characteristics consistent with the dissolution effect.

8. The method for quantitative prediction of carbonate rock dissolution intensity by well logging according to claim 1, characterized in that: The step of performing correlation screening on the obtained dissolution intensity development index parameter according to the dissolution standard sample to obtain the target dissolution intensity development index parameter comprises: obtaining candidate dissolution intensity development index parameters associated with the dissolution standard sample; According to a preset analysis strategy, the candidate dissolution intensity development index parameters are screened to obtain target dissolution intensity development index parameters.

9. The method for quantitative prediction of carbonate rock dissolution intensity by well logging according to claim 8, characterized in that: The target dissolution intensity development index parameters include at least: density logging value, neutron porosity logging value, deep resistivity logging value, microsphere resistivity logging value, and sonic time difference logging value.

10. The method for quantitative prediction of carbonate rock dissolution intensity by well logging according to claim 1, characterized in that: The method of constructing a quantitative evaluation index of dissolution intensity according to the target dissolution intensity development index parameter includes: According to the target dissolution intensity development index parameter, a multivariate linear regression strategy is adopted to construct a calculation formula for the dissolution intensity development index; Obtaining a calculation result for the dissolution intensity development index according to the calculation formula of the dissolution intensity development index, and comparing the calculation result with the intensity grade data of the associated dissolution standard sample; If the comparison results are consistent, the calculation formula of the dissolution intensity development index is determined as a quantitative evaluation index of the dissolution intensity.

11. The method for quantitative prediction of carbonate rock dissolution intensity by well logging according to claim 10, characterized in that: Also includes: According to the calculation formula of the dissolution intensity development index, a dissolution intensity quantitative evaluation curve is obtained; According to the strength grade data of the standard sample, a standard reference curve for dissolution intensity classification is obtained; Comparing the quantitative evaluation curve of dissolution intensity with the standard reference curve of dissolution intensity classification; If the comparison results are consistent, the quantitative evaluation curve of dissolution intensity is determined as the quantitative evaluation index of dissolution intensity.

12. A well logging quantitative prediction device for carbonate rock dissolution intensity, characterized in that: include: A dissolution standard sample obtaining unit, used for obtaining a dissolution standard sample associated with a target layer segment and strength grade data corresponding to the dissolution standard sample; A measurement intersection linearity processing unit, used for obtaining a measurement intersection linearity for the target layer segment according to the dissolution standard sample, and determining whether the measurement intersection linearity deviates from a preset limestone lithology line; a target dissolution intensity development index parameter obtaining unit, for, if deviated, performing correlation screening on the obtained dissolution intensity development index parameter according to the dissolution standard sample to obtain the target dissolution intensity development index parameter; The quantitative evaluation index construction unit is used to construct a quantitative evaluation index of dissolution intensity according to the target dissolution intensity development index parameter, and to quantitatively predict the dissolution intensity of the target layer segment to be measured according to the quantitative evaluation index of dissolution intensity.

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