Method and device for predicting thickness of hydrocarbon source rock, computer equipment and storage medium

Abstract

The invention provides a hydrocarbon source rock thickness prediction method and device, computer equipment and a storage medium. The method comprises the following steps: determining a depth domain longitudinal wave impedance data body corresponding to a hydrocarbon source rock in a target area; converting the depth domain longitudinal wave impedance data volume into an organic carbon content data volume; converting the depth domain longitudinal wave impedance data volume into a porosity data volume; determining the number of non-zero data in calculating the hydrocarbon source rock index factor data volume based on the organic carbon content data volume and the porosity data volume; and calculating the thickness of the hydrocarbon source rock according to the sampling spacing distance of the depth domain longitudinal wave impedance data volume and the quantity of the non-zero data, wherein the thickness of the hydrocarbon source rock is used for judging the quality of the hydrocarbon source rock. And constructing hydrocarbon source rock index factors by combining the transverse high-resolution data of the depth domain longitudinal wave impedance data body with the longitudinal high-resolution data of the drilled well, and determining the thickness of the hydrocarbon source rock according to each hydrocarbon source rock index factor. The thickness of the hydrocarbon source rock in the target area can be rapidly and scientifically calculated, and the high quality of the hydrocarbon source rock can be accurately judged.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil and gas exploration and development, and particularly relates to a method and device for predicting the thickness of source rock, a computer device and a storage medium. BACKGROUND

[0002] As a key to oil and gas formation, the accurate prediction of the thickness of source rock is of great significance to oil and gas exploration. The change of the thickness of source rock not only directly affects the generation and accumulation of hydrocarbons, but also relates to the scale and development potential of oil and gas fields.

[0003] Traditional methods for predicting the thickness of source rock mainly include seismic reflection feature analysis, sequence and system domain analysis, seismic velocity and lithology analysis, source rock maturity seismic and logging prediction, seismic attribute method, and seismic inversion method. However, due to the differences in geological conditions and the quality of seismic data in different regions, the results of different methods are quite different. Therefore, in practical applications, researchers need to combine the data and geological conditions of the target area to adopt appropriate methods, that is, different methods need to be adopted in different geological conditions in each period of oil and gas exploration, which cannot be applied to the evaluation of the development thickness of source rock in each period of oil and gas exploration, so that the quality of source rock cannot be accurately judged. SUMMARY

[0004] Therefore, it is necessary to provide a method and device for predicting the thickness of source rock, a computer device and a storage medium in view of the above technical problems.

[0005] A method for predicting the thickness of source rock comprises the following steps.

[0006] Determine the source rock of a target area and the depth domain P-wave impedance data body corresponding to the source rock, wherein the depth domain P-wave impedance data body comprises P-wave impedance values.

[0007] Convert the P-wave impedance values in the depth domain P-wave impedance data body into organic carbon content values by using a preset depth-organic carbon content conversion formula to obtain an organic carbon content data body.

[0008] Convert the P-wave impedance values in the depth domain P-wave impedance data body into porosity values by using a preset depth-porosity conversion formula to obtain a porosity data body, wherein the preset depth-porosity conversion formula is fitted based on the vitrinite reflectance, P-wave impedance value and shale porosity of source rock.

[0009] Calculate a source rock index factor data body based on the organic carbon content data body and the porosity data body, and determine the number of non-zero data in the source rock index factor data body.

[0010] determining a sampling interval distance corresponding to the depth domain P-wave impedance data body, and calculating the source rock thickness of the target area according to the sampling interval distance and the number of non-zero data.

[0011] In one embodiment, before the depth domain P-wave impedance data body is converted into the organic carbon content data body by using the preset depth-organic carbon content conversion formula, the method further comprises:

[0012] obtaining a historical P-wave impedance value of the source rock, a source rock density corresponding to the historical P-wave impedance value, and an organic carbon content of the source rock corresponding to the historical P-wave impedance value;

[0013] calculating a correlation degree between the historical P-wave impedance value and the source rock density to obtain a P-wave impedance value-density mapping relationship, and calculating a correlation degree between the historical P-wave impedance value and the organic carbon content of the source rock to obtain a P-wave impedance value-organic carbon content mapping relationship;

[0014] performing correlation degree fitting by using the P-wave impedance value-density mapping relationship and the P-wave impedance value-organic carbon content mapping relationship to obtain a preset depth-organic carbon content conversion formula.

[0015] In one embodiment, before the depth domain P-wave impedance data body is converted into the porosity data body by using the preset depth-porosity conversion formula, the method further comprises:

[0016] obtaining a vitrinite reflectance of the source rock, a historical P-wave impedance value corresponding to the vitrinite reflectance, and a historical shale porosity corresponding to the vitrinite reflectance;

[0017] calculating a correlation degree between the vitrinite reflectance and the historical shale porosity to obtain a reflectance-porosity mapping relationship, and calculating a correlation degree between the historical P-wave impedance value and the historical shale porosity to obtain a P-wave impedance value-porosity mapping relationship;

[0018] performing correlation degree fitting by combining the reflectance-porosity mapping relationship and the P-wave impedance value-porosity mapping relationship to obtain a preset depth-porosity conversion formula.

[0019] In one embodiment, the source rock index factor data body is calculated based on the organic carbon content data body and the porosity data body, comprising:

[0020] detecting whether each organic carbon content value in the organic carbon content data body is within the preset organic carbon range, and determining that the organic carbon content is a target organic carbon content when the organic carbon content is within the preset organic carbon range;

[0021] determining whether each porosity value in the porosity data volume is within the preset porosity range, and when the porosity value is within the preset porosity range, determining the porosity value as a target porosity value;

[0022] determining a first position of each target organic carbon content in the organic carbon content data volume and a second position of each target porosity value in the porosity data volume;

[0023] determining whether the coordinates of the first position and the coordinates of the second position are the same, and when the coordinates of the first position and the coordinates of the second position are the same, calculating a hydrocarbon source rock index factor based on the target organic carbon content at the first position and the target porosity value at the second position;

[0024] determining a data volume formed by each hydrocarbon source rock index factor as a hydrocarbon source rock index factor data volume.

[0025] In one embodiment, the determining of the hydrocarbon source rock of the target region and the depth domain P-wave impedance data volume corresponding to the hydrocarbon source rock comprises:

[0026] determining a hydrocarbon source rock of a target region and a post-stack migration time seismic data volume corresponding to the hydrocarbon source rock, and performing P-wave impedance inversion on the post-stack migration time seismic data volume to obtain a time domain P-wave impedance data volume;

[0027] converting the time domain P-wave impedance data volume into a depth domain P-wave impedance data volume using a preset time-depth conversion formula.

[0028] In one embodiment, the determining of the hydrocarbon source rock of the target region comprises:

[0029] determining the hydrocarbon source rock of the target region according to geological data, drilling core data and lithology interpretation data of the target region.

[0030] In one embodiment, the calculating of the hydrocarbon source rock index factor based on the target organic carbon content at the first position and the target porosity value at the second position comprises:

[0031] substituting the target organic carbon content value at the first position and the target porosity value at the second position into a preset index factor calculation formula to obtain a calculation result, and determining the calculation result as the hydrocarbon source rock index factor, wherein the preset index factor calculation formula is:

[0032]

[0033] wherein S is the hydrocarbon source rock index factor, P T is the target organic carbon content value at the first position, a target porosity value at a second location, wherein the coordinates of the first location are the same as the coordinates of the second location.

[0034] A device for predicting a source rock thickness, comprising:

[0035] A first determining module configured to determine a source rock of a target area and a depth-domain P-wave impedance data volume corresponding to the source rock, the depth-domain P-wave impedance data volume comprising P-wave impedance values;

[0036] A first converting module configured to convert the P-wave impedance values in the depth-domain P-wave impedance data volume into organic carbon content values by using a preset depth-organic carbon content conversion formula, to obtain an organic carbon content data volume;

[0037] A second converting module configured to convert the P-wave impedance values in the depth-domain P-wave impedance data volume into porosity values by using a preset depth-porosity conversion formula, to obtain a porosity data volume, the preset depth-porosity conversion formula being fitted based on vitrinite reflectance, P-wave impedance values and shale porosity of the source rock;

[0038] A second determining module configured to calculate a source rock index factor data volume based on the organic carbon content data volume and the porosity data volume, and determine a number of non-zero data in the source rock index factor data volume;

[0039] A calculating module configured to determine a sampling interval distance corresponding to the depth-domain P-wave impedance data volume, and calculate the source rock thickness of the target area according to the sampling interval distance and the number of non-zero data.

[0040] A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the prediction method of the source rock thickness in any of the above embodiments when executing the computer program.

[0041] A computer readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the steps of the prediction method of the source rock thickness in any of the above embodiments.

[0042] The prediction method, device, computer device and storage medium of the source rock thickness, by combining the lateral high resolution of the depth-domain P-wave impedance data volume with the longitudinal high resolution data of the drilling, constructing a source rock index factor, and then determining the source rock thickness according to each source rock index factor, the source rock thickness of the target area is quickly and scientifically calculated, which is helpful for accurately judging the quality of the source rock and researching and analyzing the development thickness and distribution range of the source rock. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 A flowchart of a method for predicting the thickness of a source rock in an embodiment;

[0044] Figure 2 A block diagram of an apparatus for predicting the thickness of a source rock in an embodiment;

[0045] Figure 3 An internal structure diagram of a computer device in an embodiment;

[0046] Figure 4 A schematic diagram of the characteristics of a source rock on a seismic profile in an embodiment;

[0047] Figure 5 A profile of the organic carbon content after wave impedance conversion in an embodiment;

[0048] Figure 6 A profile of the porosity after wave impedance conversion in an embodiment;

[0049] Figure 7 A schematic diagram of the thickness of high-quality source rocks in a target area in an embodiment. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0051] Embodiment One

[0052] The seismic reflection characteristic analysis method in the prior art: guided by seismic facies and sedimentary facies models, on the basis of in-depth analysis of seismic reflection characteristics, the corresponding relationship of seismic reflection structures in adjacent areas is compared and learned, or lithology data of wells in the area is used for calibration to determine the seismic reflection characteristics of the favorable hydrocarbon generation facies, and to carry out source rock identification and prediction. For low exploration areas, guided by seismic facies and sedimentary facies models, on the basis of in-depth analysis of seismic reflection characteristics, the corresponding relationship of sedimentary facies units and seismic reflection structures in adjacent areas or shallow layers is compared and learned, and the seismic reflection characteristics of the favorable hydrocarbon generation facies in the low exploration block can be determined. This method is a qualitative evaluation and is mainly applied in areas lacking drilling.

[0053] Sequence and system tract analysis: Sequence stratigraphy plays an important role in the early evaluation of source rocks. The favorable source rock development interval can be determined by using the relationship between sea / lake level change and organic matter content. In a vertical profile of a sequence, the condensed section has the highest organic matter content, and the organic matter content gradually decreases upward or downward from the condensed section. The sequence characteristics are controlled by many factors, such as tectonic movement, climate change, source supply, lake level change, etc. Any of these factors can have an important influence on the specific interval of source rock development in the sequence.

[0054] Seismic velocity lithology analysis: The velocity analysis as an intermediate step in the conventional processing of seismic data provides a large amount of velocity spectrum and stacking velocity information for lithology interpretation. Through the seismic velocity lithology quantitative interpretation technology, the formation shale index can be converted, and the total thickness of mudstone can be calculated. The seismic velocity lithology analysis method for calculating the total thickness of mudstone makes full use of the seismic velocity spectrum data, and to some extent, overcomes the difficulty of source rock evaluation in the low exploration area with few or even no wells. Although the longitudinal resolution of the velocity spectrum data is slightly lower than that of the drilling data, it is still an effective method for source rock evaluation in the low exploration area.

[0055] Ro seismic and logging prediction: There is a close relationship between the compaction degree of mudstone and thermal maturity. The mudstone porosity and vitrinite reflectance are actually the integrals of burial history over time. After the establishment of a mathematical model, if the mudstone velocity at an arbitrary depth in a low exploration area is known, the thermal maturity of the organic matter of the mudstone near the depth can be obtained. The mudstone velocity can be obtained from both the logging acoustic travel time data and the seismic velocity spectrum data. The parameters of this method are obtained empirically, and the error is large when there are few drilling wells.

[0056] Seismic attribute method: There are many seismic attributes that can be extracted from seismic data, and the information related to lithology is contained in the seismic attributes related to amplitude. Through the calibration of the synthetic record of the key well, the various seismic attributes related to amplitude of the three-dimensional seismic data in the area are extracted, the attribute profile is compared with the lithology profile of the well, and the planar distribution range of the high-quality source rock is predicted by the amplitude attribute extraction and analysis method.

[0057] Seismic inversion method: On the basis of rock physics statistics, the sandstone and mudstone wave impedance threshold value is determined, and through inversion, the sandstone and mudstone inversion lithology body can be obtained, and then the mudstone inversion body in the time domain can be obtained. On this basis, the mudstone and high-quality source rock wave impedance threshold value is determined, and through inversion, the mudstone and high-quality source rock inversion lithology body can be obtained, and then the high-quality source rock inversion body in the time domain can be obtained.

[0058] At present, there is no method for comprehensively considering the organic carbon content and vitrinite reflectance of source rock for source rock evaluation. Therefore, in the embodiment, the organic carbon content and vitrinite reflectance of source rock are comprehensively considered for source rock evaluation. Figure 1As shown, a hydrocarbon source rock thickness prediction method is provided, which comprises:

[0059] In step 110, the hydrocarbon source rock of the target area and the depth domain P-wave impedance data volume corresponding to the hydrocarbon source rock are determined, and the depth domain P-wave impedance data volume comprises P-wave impedance values.

[0060] Specifically, the distribution and characteristics of the hydrocarbon source rock of the target area are obtained, and the stratigraphic interval and range of the target area where the hydrocarbon source rock exists are determined by analyzing geological data such as sedimentary environment, stratigraphic sequence and tectonic background; further, seismic data of the target area is obtained, and the distribution, thickness and physical properties of the hydrocarbon source rock are further determined, for example, the collected original seismic data is preprocessed, including denoising, filtering, amplitude correction, etc., to improve the data quality and signal-to-noise ratio. The seismic data is stacked and processed, and the multiple excitation and reception seismic data is stacked together to enhance the effective signal and suppress random noise. The seismic data is converted from the acquisition coordinate system to the real underground coordinate system, and by applying the migration algorithm, the propagation path and speed change of the seismic wave in the underground medium can be corrected, so that the seismic data more accurately reflects the underground structure to generate the post-stack migration time seismic data volume. Finally, the time domain P-wave impedance data volume is obtained by inverting the post-stack migration time seismic data volume, and the time domain P-wave impedance data volume is converted according to the preset time-depth conversion formula to form the depth domain P-wave impedance data volume.

[0061] In this embodiment, the depth domain P-wave impedance data volume can directly reflect the physical property changes of the underground medium, especially the physical property differences of the hydrocarbon source rock. By analyzing the impedance data volume, the distribution range, thickness and physical property characteristics of the hydrocarbon source rock can be effectively identified, so as to evaluate its potential hydrocarbon generation and reservoir capacity. And the depth domain P-wave impedance data volume is part of the geophysical multi-attribute analysis. By comprehensive comparison and analysis with other seismic attributes (such as amplitude, frequency, phase, etc.) and logging data, the accuracy and reliability of oil and gas detection can be further improved.

[0062] In this embodiment, the physical property can include at least one of P-wave velocity and impedance, which is not limited here.

[0063] In step 120, the P-wave impedance values in the depth domain P-wave impedance data volume are converted into organic carbon content values by using a preset depth-organic carbon content conversion formula to obtain an organic carbon content data volume.

[0064] In this embodiment, the depth domain P-wave impedance data volume mainly reflects the physical properties of the underground medium, and the organic carbon content provides information about the chemical properties of the rock. In order to more accurately identify the distribution and characteristics of the hydrocarbon source rock, the depth domain P-wave impedance data volume is converted into the organic carbon content data volume.

[0065] Specifically, each data point in the depth domain P-wave impedance data body is determined, the data point is substituted into the preset depth-TOC conversion formula for conversion, and a TOC value corresponding to the P-wave impedance value of the data point is obtained, so that a TOC data body is formed. For example, a data point in the depth domain P-wave impedance data body is represented as {x i → AI i}, where x i represents depth, and AI i represents the P-wave impedance value; the P-wave impedance value in the data point is substituted into the preset depth-TOC conversion formula for conversion, and a TOC value corresponding to the P-wave impedance value of the data point is obtained. A data point in the TOC data body is represented as {x i → TOC i}, where x i represents depth, and TOC i represents the TOC value.

[0066] In one embodiment, the preset density-TOC conversion formula is:

[0067]

[0068] wherein AI is the P-wave impedance value, p is the density, AC is the P-wave interval travel time, TOC is the TOC value, and m is a constant coefficient of the TOC value, and n is an exponential coefficient of the TOC value.

[0069] In one embodiment, the preset density-TOC conversion formula is:

[0070]

[0071] wherein AI is the P-wave impedance value, p is the density, AC is the P-wave interval travel time, and TOC is the TOC value.

[0072] In step 130, the P-wave impedance value in the depth domain P-wave impedance data body is converted into a porosity value by using a preset depth-porosity conversion formula, so that a porosity data body is obtained, and the preset depth-porosity conversion formula is fitted based on the vitrinite reflectance, the P-wave impedance value, and the porosity of the mudstone of the source rock.

[0073] In this embodiment, specifically, before the conversion, the depth domain P-wave impedance data body needs to be preprocessed to eliminate or reduce the influence of noise, outliers, and non-geological factors. The preprocessing can include at least one of filtering, smoothing, interpolation, and the like. Each data point in the preprocessed depth domain P-wave impedance data body is substituted into the preset depth-porosity conversion formula, and a porosity value corresponding to the P-wave impedance value of the data point is obtained, so that a porosity data body is formed. For example, a data point in the depth domain P-wave impedance data body is represented as {x i → AIi}, wherein x i represents the depth, AI i represents the P-wave impedance value; the P-wave impedance value in the data point is substituted into the preset depth-porosity conversion formula for conversion, and the P-wave impedance value thereof is converted into the corresponding porosity. The data point in the porosity data body is represented as wherein x i represents the depth, represents the porosity.

[0074] In one embodiment, the preset depth-porosity conversion formula is:

[0075]

[0076] wherein, R o the vitrinite reflectance of the source rock, is the shale porosity, AI is the P-wave impedance value, A is the first constant coefficient of porosity, B is the exponential constant coefficient of porosity, C is the second constant coefficient of porosity, and D is the compensation constant coefficient.

[0077] In one embodiment, the preset depth-porosity conversion formula is:

[0078]

[0079] wherein, R o the vitrinite reflectance of the source rock, is the shale porosity, and AI is the P-wave impedance value.

[0080] In one embodiment, the preset density-porosity conversion formula is obtained by correlation fitting in combination with the reflectivity-porosity mapping relationship formula and the P-wave impedance value-porosity mapping relationship formula, wherein the P-wave impedance value-porosity mapping relationship formula is:

[0081] In one embodiment, the reflectivity-porosity mapping relationship formula is:

[0082]

[0083] wherein, R o the vitrinite reflectance of the source rock, is the shale porosity, A is the first constant coefficient of porosity, and B is the exponential constant coefficient of porosity.

[0084] In one embodiment, the vitrinite reflectance-porosity mapping relationship formula is:

[0085]

[0086] wherein, R o the vitrinite reflectance of the source rock, porosity of mudstone.

[0087] In one embodiment, the mapping relationship between the P-wave impedance value and the porosity is:

[0088]

[0089] wherein, porosity of mudstone, AI is the P-wave impedance value, C is the second constant coefficient of porosity, and D is the compensation constant coefficient.

[0090] In one embodiment, the mapping relationship between the P-wave impedance value and the porosity is:

[0091]

[0092] wherein, porosity of mudstone, and AI is the P-wave impedance value.

[0093] Step 140, calculating a source rock index factor data body based on the organic carbon content data body and the porosity data body, and determining the number of non-zero data in the source rock index factor data body.

[0094] By integrating the organic carbon content and porosity data, the quality of the source rock and the hydrocarbon generation potential can be more accurately depicted. The combination of the organic carbon content data body and the porosity data body can make full use of the information of the two different types of data, and provide a data basis for more accurate and comprehensive calculation of the source rock thickness.

[0095] In the embodiment, the process of calculating the source rock index factor data body specifically includes: standardizing each data point in the organic carbon content data body and each data point in the porosity data body to eliminate the influence of different dimensions or units. Then it is determined that the organic carbon content data body and the porosity data body are aligned in space, i.e. they have the same grid system or coordinate system, so as to be able to directly correspond to each data point. The first position of each data point in the organic carbon content data body is determined, and the second position of each data point in the porosity data body is determined; when the first position is the same as the second position, the product between the organic carbon content value at the first position and the porosity at the second position is calculated, and the product is taken as the data point in the source rock index factor data body. The position of the data point in the source rock index factor data body is the first position (or the second position).

[0096] When the source rock index factor data body is calculated, the number of source rock index factors that are not zero in the source rock index factor data body is determined, which provides a data basis for calculating the source rock thickness in step 150.

[0097] Step 150, determining the sampling interval distance corresponding to the depth domain P-wave impedance data body, and calculating the source rock thickness of the target area according to the sampling interval distance and the number of non-zero data.

[0098] In the embodiment, when the source rock index factor of the data point in the source rock index factor data body is zero, it indicates that there is no source rock at the position; when the source rock index factor of the data point in the source rock index factor data body is not zero, it indicates that there is source rock at the position. Therefore, after determining the number of source rock index factors that are not zero in the source rock index factor data body, the source rock thickness is further calculated, specifically: determining the sampling interval distance corresponding to the depth domain P-wave impedance data body; the sampling interval distance represents the density and resolution of the data point. Then, the position coordinates of the non-zero data points of the source rock index factor data body are determined, and the maximum distance of the adjacent non-zero data points in the vertical direction is calculated, that is, the product of the sampling interval distance and the non-zero data in the vertical direction is calculated, and the product is taken as the source rock thickness, which is used to judge the quality of the source rock.

[0099] In one embodiment, the source rock thickness can be used to judge the quality of the source rock.

[0100] In the embodiment, the source rock index factor is constructed by combining the lateral high resolution of the depth domain P-wave impedance data body and the vertical high resolution data of the well, and then the quality source rock thickness is determined according to each source rock index factor. The quality source rock thickness of the target area is quickly and scientifically calculated, which is helpful for studying and analyzing the development thickness and distribution range of the quality source rock.

[0101] It should be understood that, although Figure 1 The steps in the flowchart of the method are displayed in sequence according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps in the method can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily sequential, but can be executed in rotation or alternation with other steps or at least part of the sub-steps or stages of other steps.

[0102] In one embodiment, before the depth domain P-wave impedance data body is converted into the porosity data body by using the preset depth-porosity conversion formula, the method further includes:

[0103] 1-1) obtaining vitrinite reflectance of the source rock, a historical P-wave impedance value corresponding to the vitrinite reflectance, and a historical shale porosity corresponding to the vitrinite reflectance.

[0104] In the embodiment, the source rock in the target area is determined, and then source rock data corresponding to the source rock is obtained, the source rock data including vitrinite reflectance, a historical P-wave impedance value corresponding to the vitrinite reflectance, a historical shale porosity corresponding to the vitrinite reflectance, source rock density corresponding to the historical P-wave impedance value, and source rock organic carbon content corresponding to the historical P-wave impedance value, and the like. Therefore, the vitrinite reflectance of the source rock, the historical P-wave impedance value corresponding to the vitrinite reflectance, and the historical shale porosity corresponding to the vitrinite reflectance can be screened from the source rock data. The screened historical P-wave impedance value has the representative of the rock type corresponding to the source rock, and the historical P-wave impedance value should have a good correlation with the maturity of the source rock, such as vitrinite reflectance.

[0105] In the embodiment, the source rock data corresponding to the source rock can be obtained from a storage medium or from the cloud, which is not limited here.

[0106] 1-2) calculating the correlation between the vitrinite reflectance and the historical shale porosity to obtain a reflectance-porosity mapping relationship, and calculating the correlation between the historical P-wave impedance value and the historical shale porosity to obtain a P-wave impedance value-porosity mapping relationship.

[0107] 1-3) fitting the correlation based on the reflectance-porosity mapping relationship and the P-wave impedance value-porosity mapping relationship to obtain a preset depth-porosity conversion formula.

[0108] In the embodiment, vitrinite reflectance is the most important organic matter maturity index, which is used to calibrate the thermal evolution process of organic matter from early diagenesis to deep metamorphic stage. Porosity is the proportion of pore space in rock. By combining vitrinite reflectance to determine the preset depth-porosity conversion formula, the physical properties of rock, porosity distribution, and depth change and other factors can be considered comprehensively, thereby improving the accuracy and reliability of the preset depth-porosity conversion formula.

[0109] In one embodiment, before the depth domain P-wave impedance data volume is converted into an organic carbon content data volume by using the preset depth-organic carbon content conversion formula, the method further includes:

[0110] 2-1) obtaining a historical P-wave impedance value of the source rock, source rock density corresponding to the historical P-wave impedance value, and source rock organic carbon content corresponding to the historical P-wave impedance value.

[0111] In the embodiment, the source rock in the target area is determined, and then source rock data corresponding to the source rock is obtained, the source rock data including vitrinite reflectance, historical P-wave impedance value corresponding to the vitrinite reflectance, historical shale porosity corresponding to the vitrinite reflectance, source rock density corresponding to the historical P-wave impedance value, and source rock organic carbon content corresponding to the historical P-wave impedance value, and the like. Therefore, the source rock density corresponding to the historical P-wave impedance value of the source rock and the source rock organic carbon content corresponding to the historical P-wave impedance value can be screened out from the source rock data. The screened historical P-wave impedance value has the representative of the rock type corresponding to the source rock, and the historical P-wave impedance value should have a good correlation with the organic carbon content of the source rock.

[0112] In the embodiment, the source rock data corresponding to the source rock can be obtained from a storage medium or from the cloud, which is not limited here.

[0113] 2-2) Calculate the correlation between the historical P-wave impedance value and the source rock density to obtain a P-wave impedance value-density mapping relationship, and calculate the correlation between the historical P-wave impedance value and the source rock organic carbon content to obtain a P-wave impedance value-organic carbon content mapping relationship.

[0114] 2-3) Correlation fitting is performed using the P-wave impedance value-density mapping relationship and the P-wave impedance value-organic carbon content mapping relationship to obtain a preset depth-organic carbon content conversion formula.

[0115] In the embodiment, the preset depth-organic carbon content conversion formula is determined by combining the organic carbon content, which can comprehensively consider various factors of the source rock, such as organic matter type, maturity, and deposition environment, thereby improving the accuracy and reliability of the preset depth-organic carbon content conversion formula.

[0116] In one embodiment, the source rock index factor data body is calculated based on the organic carbon content data body and the porosity data body, including:

[0117] 3-1) Detect whether each organic carbon content value in the organic carbon content data body is in the preset organic carbon range. When the organic carbon content is in the preset organic carbon range, it is determined that the organic carbon content is a target organic carbon content.

[0118] In the embodiment, the preset organic carbon range is:

[0119]

[0120] P TAn organic carbon content value corresponding to a data point in the organic carbon content data body.

[0121] 3-2) Determine whether each porosity value in the porosity data body is in the preset porosity range, and when the porosity value is in the preset porosity range, determine the porosity value as a target porosity value.

[0122] In this embodiment, the preset porosity range is:

[0123]

[0124] An organic carbon content value corresponding to a data point in the organic carbon content data body. An organic carbon content value corresponding to a data point in the organic carbon content data body.

[0125] 3-3) Determine a first position of each of the target organic carbon content in the organic carbon content data body, and a second position of each of the target porosity value in the porosity data body.

[0126] 3-4) Determine whether the coordinates of the first position and the coordinates of the second position are the same, and when the coordinates of the first position and the coordinates of the second position are the same, calculate a source rock index factor based on the target organic carbon content at the first position and the target porosity value at the second position.

[0127] 3-5) Determine a data body formed by each of the source rock index factors as a source rock index factor data body.

[0128] In this embodiment, the organic carbon content of different source rocks is different, and therefore, limiting the range of organic carbon content helps to screen out source rocks with actual hydrocarbon generation potential and avoid including non-source rocks or rocks with small hydrocarbon generation potential in the calculation. Higher porosity means lower vitrinite reflectance, which reflects that the maturity of the source rock is lower and is not conducive to the generation of oil and gas. Therefore, the description accuracy of the calculated source rock index factor data body is higher and more in line with the actual situation, and the source rock thickness calculated based on the source rock data body is more accurate.

[0129] In one embodiment, the determination of the source rock of the target area and the depth domain P-wave impedance data body corresponding to the source rock comprises:

[0130] 4-1) Determine the source rock of the target area and the post-stack migration time seismic data body corresponding to the source rock, and perform P-wave impedance inversion on the post-stack migration time seismic data body to obtain a time domain P-wave impedance data body.

[0131] In this embodiment, the post-stack migration time seismic data volume is a series of processed seismic data, including stacking, migration and other steps, to more accurately reflect the subsurface structure and lithology information. After obtaining the post-stack migration time seismic data volume, the post-stack migration time seismic data volume is substituted into the P-wave impedance inversion formula to calculate the time-domain P-wave impedance data volume.

[0132] In this embodiment, the P-wave impedance inversion formula is as follows:

[0133]

[0134] wherein, I t is the time-domain P-wave impedance data volume, I t0 is the post-stack migration time seismic data volume, and t is the migration time.

[0135] 4-2) Convert the time-domain P-wave impedance data volume into a depth-domain P-wave impedance data volume using a preset time-depth conversion formula.

[0136] Then, the time-domain P-wave impedance data volume is substituted into the preset time-depth conversion formula to calculate the depth-domain P-wave impedance data volume. In this embodiment, the time-depth conversion formula is:

[0137] D = 2441.2 0.

[0138] wherein, D is the vertical depth, and T is the two-way travel time.

[0139] In this embodiment, after converting the time-domain data into depth-domain data, it can be directly compared and analyzed with other depth-domain data (such as logging data, geological model, etc.), further revealing the characteristics and variation rules of the subsurface geological structure.

[0140] In one embodiment, the determination of the source rock of the target area comprises:

[0141] 5-1) According to the geological data, drilling core data and lithology interpretation data of the target area, the source rock of the target area is determined.

[0142] In this embodiment, combining multiple data sources (geological data, drilling core data, lithology data) can more comprehensively understand the geological characteristics and distribution of source rocks in the target area. These data can be verified and supplemented with each other, thereby reducing the errors that may be caused by a single data source and improving the accuracy and reliability of source rock identification.

[0143] In one embodiment, the calculation of the source rock index factor based on the target organic carbon content at the first position and the target porosity value at the second position comprises:

[0144] 6-1) substituting the target organic carbon content value at the first position and the target porosity value at the second position into a preset index factor calculation formula to calculate a calculation result, and determining the calculation result as the source rock index factor, wherein the preset index factor calculation formula is:

[0145]

[0146] wherein S is the source rock index factor, P T is the target organic carbon content value at the first position, is the target porosity value at the second position, wherein the coordinates of the first position are the same as the coordinates of the second position.

[0147] In the present embodiment, after the first position and the second position are defined to be the same, the target organic carbon content value at the first position and the target porosity value at the second position are used to calculate the source rock index factor, so as to ensure the accuracy of the distribution of the finally formed source rock index factor data volume.

[0148] Embodiment two

[0149] In the present embodiment, a method for predicting the thickness of source rock is provided, which comprises:

[0150] Step 210: collecting the basic data of the target area, including regional geological data, post-stack migration time seismic data volume, all stratigraphic layers of the drilling wells in the target area, logging P-wave curve, logging density curve, lithology interpretation column, drilling core organic carbon content TOC and vitrinite reflectance R0. In the present embodiment, the target area is a certain basin in Brazil.

[0151] Step 220: determining the main source rock layer according to the geological data, drilling core and lithology interpretation column of the target area. For example, when the target area is a certain basin in Brazil, the main source rock layer of the certain basin in Brazil can be determined as Cretaceous Aptian delta mudstone by analyzing the geological data, drilling core and lithology interpretation column of the certain basin in Brazil.

[0152] Step 230: making a synthetic record according to the stratigraphic layers of the drilling wells, logging P-wave and density curves of the target area; calibrating the synthetic record in time domain and depth domain to obtain a drilling time-depth pair; and determining the seismic reflection interface feature of the main source rock layer as strong seismic axis amplitude and good continuity, as shown in FIG. 2. Figure 4

[0153] ​Step 240, according to the seismic reflection interface characteristics of the hydrocarbon source rock layer, seismic interpretation is carried out on the post-stack migration time seismic data volume, and the top surface time T0 and the bottom surface time T1 of the whole area hydrocarbon source rock layer are tracked out; the top surface time T0 and the bottom surface time T1 are obtained by the preset time-depth conversion formula (1) to obtain the top surface depth D0 and the bottom surface depth D1. In the preset time-depth conversion formula (1), D is the vertical depth, and T is the two-way travel time, which is fitted according to the drilling time-depth.

[0154] D = 2441.2 0.2455 (1)

[0155] Step 250, according to the P-wave and density curve of the drilling in the target area, the P-wave impedance value-density mapping relationship is calculated, and the P-wave impedance value-density mapping relationship formula (2) is obtained, wherein p is the density, and AC is the P-wave acoustic time difference.

[0156]

[0157] Step 260, the preset depth-organic carbon content conversion formula is fitted according to the P-wave impedance value-organic carbon content mapping relationship formula (3) and the P-wave impedance value-density mapping relationship formula (2), wherein the P-wave impedance value-organic carbon content conversion formula (10) is obtained.

[0158] AI = 5269 -0.178 (3)

[0159] Wherein, TOC is the organic carbon content, and AI is the P-wave impedance value.

[0160]

[0161] Wherein, AC is the P-wave acoustic time difference, TOC is the organic carbon content, and AI is the P-wave impedance value.

[0162] Step 270, according to the P-wave impedance inversion formula (4), P-wave impedance inversion is carried out on the post-stack migration time seismic data volume, and the time domain P-wave impedance data volume I t is obtained. According to the preset time-depth conversion formula (1), the time domain P-wave impedance data volume I t is converted into the depth domain P-wave impedance data volume I d . According to the preset depth-organic carbon content conversion formula (3), the depth domain P-wave impedance data volume I d is converted into the TOC data volume P T , as shown in Figure 5 .

[0163] In this embodiment, the P-wave impedance inversion formula (4) is as follows:

[0164]

[0165] Among them, I t For time-domain longitudinal wave impedance data volume, I t0 This is the post-stack migration time seismic data volume, where t is the migration time.

[0166] Step 280, Reflectance-Porosity Mapping Equation (5), derived from the reflectance Ro of the vitrinite source rock in the well and the porosity of the mudstone. The result was obtained through fitting. When Ro is 0.6%, the threshold value for porosity is determined to be 9%.

[0167]

[0168] Among them, R o The reflectance of the vitrinite in the source rock. This refers to the porosity of mudstone.

[0169] Step 290: Combine the reflectivity-porosity mapping relationship and the longitudinal wave impedance-porosity mapping relationship (6) to perform correlation fitting and obtain the preset depth-porosity conversion formula (7).

[0170]

[0171] in, The value represents the porosity of the mudstone and the longitudinal wave impedance (AI).

[0172]

[0173] Among them, R o The reflectance of vitrinite in source rocks. The value represents the porosity of the mudstone and the longitudinal wave impedance (AI).

[0174] Step 210: According to the preset depth-porosity conversion formula (7), convert the depth domain impedance data volume I. d Convert to porosity data volume like Figure 6 As shown.

[0175] Step 211: Construct the source rock index factor S, and the calculation formula is (8).

[0176]

[0177] in

[0178] Step 212: Calculate the source rock index factor S data volume according to equation (8), count the number of non-zero grid points L in each top and bottom surface of the S data volume, and obtain the thickness of the high-quality source rock according to equation (9). Figure 7 As shown, R is the sampling interval of 5m.

[0179] H = L * R (9)

[0180] In the embodiment, the method for predicting the thickness of the source rock is applicable to various stages of oil and gas exploration, especially in the early exploration stage. When the study area is a new exploration area and there are few drilling and core data, the method can make full use of the lateral high resolution of the seismic data and the vertical high resolution of the drilling data to construct a source rock index factor, quickly and scientifically judge whether there is high-quality source rock in the area, and help geologists to study and analyze the development thickness and distribution range of the high-quality source rock in the main target layer of the area, and evaluate the oil and gas exploration potential of the area in combination with other oil and gas conditions.

[0181] Embodiment three

[0182] In the embodiment, as shown in Figure 2 , a device for predicting the thickness of a source rock is provided, comprising:

[0183] A first determination module 310 is configured to determine a source rock in a target area and a depth-domain P-wave impedance data body corresponding to the source rock, wherein the depth-domain P-wave impedance data body comprises P-wave impedance values.

[0184] A first conversion module 320 is configured to convert the P-wave impedance values in the depth-domain P-wave impedance data body into organic carbon content values by using a preset depth-organic carbon content conversion formula, to obtain an organic carbon content data body.

[0185] A second conversion module 330 is configured to convert the P-wave impedance values in the depth-domain P-wave impedance data body into porosity values by using a preset depth-porosity conversion formula, to obtain a porosity data body, wherein the preset depth-porosity conversion formula is fitted based on the vitrinite reflectance of the source rock, the P-wave impedance values, and the porosity of the mudstone.

[0186] A second determination module 340 is configured to calculate a source rock index factor data body based on the organic carbon content data body and the porosity data body, and determine the number of non-zero data in the source rock index factor data body.

[0187] A calculation module 350 is configured to determine a sampling interval distance corresponding to the depth-domain P-wave impedance data body, and calculate the thickness of the source rock in the target area according to the sampling interval distance and the number of non-zero data.

[0188] In the embodiment, the first determining module 310 determines the hydrocarbon source rock of the target area and a depth domain P-wave impedance data body corresponding to the hydrocarbon source rock, the depth domain P-wave impedance data body comprising P-wave impedance values, and sends the depth domain P-wave impedance data body to the first conversion module 320 and the second conversion module 330. The first conversion module 320 converts the P-wave impedance values in the depth domain P-wave impedance data body into organic carbon content values by using a preset depth-organic carbon content conversion formula, obtains an organic carbon content data body, and sends the organic carbon content data body to the second determining module 340. The second conversion module 330 converts the P-wave impedance values in the depth domain P-wave impedance data body into porosity values by using a preset depth-porosity conversion formula, obtains a porosity data body, and finally sends the porosity data body to the second determining module 340, wherein the preset depth-porosity conversion formula is fitted based on the vitrinite reflectance of the hydrocarbon source rock, the P-wave impedance values and the shale porosity. The second determining module 340 calculates a hydrocarbon source rock index factor data body based on the organic carbon content data body and the porosity data body, determines the number of non-zero data in the hydrocarbon source rock index factor data body, and then sends the number of non-zero data to the calculation module 350. The calculation module 350 determines the sampling interval distance corresponding to the depth domain P-wave impedance data body, and calculates the hydrocarbon source rock thickness of the target area according to the sampling interval distance and the number of non-zero data.

[0189] In the embodiment, the hydrocarbon source rock index factor is constructed by combining the lateral high resolution of the depth domain P-wave impedance data body with the longitudinal high resolution data of the well, and then the hydrocarbon source rock thickness is determined according to each hydrocarbon source rock index factor. The hydrocarbon source rock thickness of the target area is quickly and scientifically calculated, which is helpful for accurately judging the quality of the hydrocarbon source rock and analyzing the development thickness and distribution range of the hydrocarbon source rock.

[0190] In one embodiment, the hydrocarbon source rock thickness prediction device can further comprise a first obtaining module, a first relationship formula calculation module and a third determining module.

[0191] The first obtaining module is configured to obtain the vitrinite reflectance of the hydrocarbon source rock, the historical P-wave impedance value corresponding to the vitrinite reflectance, and the historical shale porosity corresponding to the vitrinite reflectance.

[0192] The first relationship formula calculation module is configured to calculate the correlation degree between the vitrinite reflectance and the historical shale porosity to obtain a reflectance-porosity mapping relationship, and calculate the correlation degree between the historical P-wave impedance value and the historical shale porosity to obtain a P-wave impedance value-porosity mapping relationship.

[0193] The third determining module is configured to perform correlation fitting on the reflectivity-porosity mapping relationship and the P-wave impedance value-porosity mapping relationship to obtain a preset depth-porosity conversion formula.

[0194] In one embodiment, the device for predicting the thickness of the source rock can further include a second obtaining module, a second relationship calculation module, and a fourth determining module.

[0195] The second obtaining module is configured to obtain a historical P-wave impedance value of the source rock, a density of the source rock corresponding to the historical P-wave impedance value, and an organic carbon content of the source rock corresponding to the historical P-wave impedance value.

[0196] The second relationship calculation module is configured to calculate a correlation degree between the historical P-wave impedance value and the density of the source rock to obtain a P-wave impedance value-density mapping relationship, and calculate a correlation degree between the historical P-wave impedance value and the organic carbon content of the source rock to obtain a P-wave impedance value-organic carbon content mapping relationship.

[0197] The fourth determining module is configured to perform correlation fitting on the P-wave impedance value-density mapping relationship and the P-wave impedance value-organic carbon content mapping relationship to obtain a preset depth-organic carbon content conversion formula.

[0198] In one embodiment, the second determining module 340 can include a first detecting unit, a second detecting unit, a first determining unit, a calculation unit, and a second determining unit.

[0199] The first detecting unit is configured to detect whether each organic carbon content value in the organic carbon content data body is within the preset organic carbon range, and when the organic carbon content is within the preset organic carbon range, determine the organic carbon content as a target organic carbon content.

[0200] The second detecting unit is configured to detect whether each porosity value in the porosity data body is within the preset porosity range, and when the porosity value is within the preset porosity range, determine the porosity value as a target porosity value.

[0201] The first determining unit is configured to determine a first position of each target organic carbon content in the organic carbon content data body and a second position of each target porosity value in the porosity data body.

[0202] The calculation unit is configured to detect whether the coordinates of the first position and the coordinates of the second position are the same, and when the coordinates of the first position and the coordinates of the second position are the same, calculate a source rock index factor based on the target organic carbon content at the first position and the target porosity value at the second position.

[0203] The second determining unit is configured to determine a data volume formed by each of the hydrocarbon source rock index factors as a hydrocarbon source rock index factor data volume.

[0204] In one embodiment, the first determining module 310 can include a third determining unit, a converting unit and a fourth determining unit.

[0205] The third determining unit is configured to determine a hydrocarbon source rock of a target area and a post-stack migration time seismic data volume corresponding to the hydrocarbon source rock, perform P-wave impedance inversion on the post-stack migration time seismic data volume to obtain a time-domain P-wave impedance data volume.

[0206] The converting unit is configured to convert the time-domain P-wave impedance data volume into a depth-domain P-wave impedance data volume by using a preset time-depth conversion formula.

[0207] In one embodiment, the first determining module 310 can further include:

[0208] The fourth determining unit is configured to determine the hydrocarbon source rock of the target area according to geological data, drilling core data and lithology interpretation data of the target area.

[0209] In one embodiment, the calculating unit is further configured to substitute the target organic carbon content value at the first position and the target porosity value at the second position into a preset index factor calculation formula to obtain a calculation result, and determine the calculation result as the hydrocarbon source rock index factor, wherein the preset index factor calculation formula is:

[0210]

[0211] wherein S is the hydrocarbon source rock index factor, P T is the target organic carbon content value at the first position, is the target porosity value at the second position, wherein the coordinates of the first position are the same as the coordinates of the second position.

[0212] The specific limitations of the prediction device for the thickness of the hydrocarbon source rock can refer to the limitations of the prediction method for the thickness of the hydrocarbon source rock in the above, which will not be repeated here. Each unit in the prediction device for the thickness of the hydrocarbon source rock can be realized by software, hardware and combinations thereof, in whole or in part. Each unit described above can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to each unit.

[0213] Embodiment Four

[0214] In this embodiment, a computer device is provided. Its internal structure diagram can be as shown in Figure 3As shown in the figure. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium, an internal memory. The non-volatile storage medium stores an operating system and a computer program, and the non-volatile storage medium is deployed with a database for storing all related data involved in the prediction method of the thickness of the hydrocarbon source rock. The internal memory provides an environment for the running of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with other computer devices deployed with application software. The computer program is executed by the processor to implement a prediction method of the thickness of the hydrocarbon source rock. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad or mouse, etc.

[0215] Those skilled in the art can understand that, Figure 3 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0216] In one embodiment, a computer device is provided, including a memory storing a computer program and a processor executing the computer program to implement the steps of the prediction method of the thickness of the hydrocarbon source rock described in any of the above embodiments.

[0217] Embodiment five

[0218] In this embodiment, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by the processor to implement the steps of the prediction method of the thickness of the hydrocarbon source rock described in any of the above embodiments.

[0219] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, databases, or other media in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0220] The technical features of the above embodiments can be combined in any way. In order to make the description simple, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not exist, they should be considered as the scope of the present application.

[0221] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, some modifications and improvements can be made, which are all within the scope of the present application. Therefore, the scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method of predicting the thickness of a source rock of hydrocarbons, characterized in that, The method comprises the following steps: determining the hydrocarbon source rock of the target area and the depth domain P-wave impedance data volume corresponding to the hydrocarbon source rock, wherein the depth domain P-wave impedance data volume comprises P-wave impedance values; converting the P-wave impedance values in the depth domain P-wave impedance data volume into organic carbon content values by using a preset depth-organic carbon content conversion formula, to obtain an organic carbon content data volume; converting the P-wave impedance values in the depth domain P-wave impedance data volume into porosity values by using a preset depth-porosity conversion formula, to obtain a porosity data volume, wherein the preset depth-porosity conversion formula is fitted based on the vitrinite reflectance of the hydrocarbon source rock, the P-wave impedance values and the shale porosity; calculating a hydrocarbon source rock index factor data volume based on the organic carbon content data volume and the porosity data volume, and determining the number of non-zero data in the hydrocarbon source rock index factor data volume; determining the sampling interval distance corresponding to the depth domain P-wave impedance data volume, and calculating the thickness of the hydrocarbon source rock of the target area according to the sampling interval distance and the number of non-zero data.

2. The method of claim 1, wherein, Before the depth domain P-wave impedance data volume is converted into the organic carbon content data volume by using the preset depth-organic carbon content conversion formula, the method further comprises the following steps: obtaining the historical P-wave impedance value of the hydrocarbon source rock, the hydrocarbon source rock density corresponding to the historical P-wave impedance value and the hydrocarbon source rock organic carbon content corresponding to the historical P-wave impedance value; calculating the correlation degree between the historical P-wave impedance value and the hydrocarbon source rock density, to obtain a P-wave impedance value-density mapping relationship, and calculating the correlation degree between the historical P-wave impedance value and the hydrocarbon source rock organic carbon content, to obtain a P-wave impedance value-organic carbon content mapping relationship; performing correlation degree fitting by using the P-wave impedance value-density mapping relationship and the P-wave impedance value-organic carbon content mapping relationship, to obtain the preset depth-organic carbon content conversion formula.

3. The method of claim 1, wherein, Before the depth domain P-wave impedance data volume is converted into the porosity data volume by using the preset depth-porosity conversion formula, the method further comprises the following steps: obtaining the vitrinite reflectance of the hydrocarbon source rock, the historical P-wave impedance value corresponding to the vitrinite reflectance and the historical shale porosity corresponding to the vitrinite reflectance; calculating the correlation degree between the vitrinite reflectance and the historical shale porosity, to obtain a reflectance-porosity mapping relationship, and calculating the correlation degree between the historical P-wave impedance value and the historical shale porosity, to obtain a P-wave impedance value-porosity mapping relationship; performing correlation degree fitting by combining the reflectance-porosity mapping relationship and the P-wave impedance value-porosity mapping relationship, to obtain the preset depth-porosity conversion formula.

4. The method of claim 1, wherein, The method for calculating the hydrocarbon source rock index factor data volume based on the organic carbon content data volume and the porosity data volume comprises the following steps: detecting whether each organic carbon content value in the organic carbon content data volume is within the preset organic carbon range, and determining the organic carbon content as a target organic carbon content when the organic carbon content is within the preset organic carbon range; detecting whether each porosity value in the porosity data volume is within the preset porosity range, and determining the porosity value as a target porosity value when the porosity value is within the preset porosity range; determining a first position of each of the target organic carbon content in the organic carbon content data body and a second position of each of the target porosity value in the porosity data body; detecting whether the coordinates of the first position and the coordinates of the second position are the same, and when the coordinates of the first position and the coordinates of the second position are the same, calculating a source rock index factor based on the target organic carbon content at the first position and the target porosity value at the second position; determining a data body formed by each of the source rock index factors as a source rock index factor data body.

5. The method of claim 4, wherein, The calculating of the source rock index factor based on the target organic carbon content at the first position and the target porosity value at the second position comprises: substituting the target organic carbon content value at the first position and the target porosity value at the second position into a preset index factor calculation formula to calculate a calculation result, and determining the calculation result as the source rock index factor, wherein the preset index factor calculation formula is: where S is a source rock index factor, P T is a target organic carbon content value at a first location, is a target porosity value at a second location, where the coordinates of the first location are the same as the coordinates of the second location.

6. The method of claim 1, wherein, The determining of the source rock of the target region and the depth domain P-wave impedance data body corresponding to the source rock comprises: determining a source rock of a target region and a post-stack migration time seismic data body corresponding to the source rock, and performing P-wave impedance inversion on the post-stack migration time seismic data body to obtain a time domain P-wave impedance data body; converting the time domain P-wave impedance data body into a depth domain P-wave impedance data body by using a preset time-depth conversion formula.

7. The method of claim 1, wherein, The determining of the source rock of the target region comprises: determining the source rock of the target region according to geological data, drilling core data and lithology analysis data of the target region.

8. A device for predicting the thickness of a source rock of hydrocarbons, characterized in that, comprises: a first determining module configured to determine a source rock of a target region and a depth domain P-wave impedance data body corresponding to the source rock, the depth domain P-wave impedance data body comprising P-wave impedance values; a first converting module configured to convert the P-wave impedance values in the depth domain P-wave impedance data body into organic carbon content values by using a preset depth-organic carbon content conversion formula to obtain an organic carbon content data body; a second converting module configured to convert the P-wave impedance values in the depth domain P-wave impedance data body into porosity values by using a preset depth-porosity conversion formula to obtain a porosity data body, the preset depth-porosity conversion formula being fitted based on vitrinite reflectance of source rock, P-wave impedance values and mudstone porosity; a second determining module configured to calculate a source rock index factor data body based on the organic carbon content data body and the porosity data body, and determine a number of non-zero data in the source rock index factor data body; a calculating module configured to determine a sampling interval distance corresponding to the depth domain P-wave impedance data body, and calculate a source rock thickness of the target region according to the sampling interval distance and the number of non-zero data. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor executes the computer program to realize the steps of the method in any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the method in any one of claims 1 to 7.

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