Prediction method of organic matter abundance of mud shale in low exploration degree area

Abstract

The present application provides a kind of low exploration degree area mud shale organic matter abundance prediction method, comprising: step 1: determine the distribution of each strata layer system and sedimentary center;Step 2: carry out sedimentary facies, element and organic matter abundance related geochemical analysis test;Step 3: establish the change model of different sample points deposition rate;Step 4: establish the change model of each sample point paleo-productivity;Step 5: evaluate the change model of each sample point redox degree;Step 6: establish the correlation model of each sedimentary environment index and organic matter abundance;Step 7: establish the quantitative prediction model of the applicable multi-element organic matter abundance of the study area;Step 8: predict the planar distribution of organic matter abundance.The low exploration degree area mud shale organic matter abundance prediction method improves the precision of mud shale quality prediction, and lays a solid theoretical basis for continental lacustrine basin hydrocarbon source rock evaluation, oil and gas distribution rule and shale oil and gas exploration and development.

Description

Technical Field

[0001] This invention relates to the field of oilfield exploration and development technology, and in particular to a method for predicting the organic matter abundance of mudstone and shale in low-exploration areas. Background Technology

[0002] Continental oil and gas exploration practices have shown that oil and gas distribution is mainly controlled by source rock conditions, among which the organic matter abundance of source rocks plays a key role and is an important factor in oil and gas accumulation conditions. Due to the rapid sedimentary facies changes and complex organic matter composition of continental source rocks, predicting the organic matter abundance of source rocks is difficult, which to some extent hinders the prediction of oil and gas resource potential and exploration deployment.

[0003] my country possesses abundant oil and gas resources in low-exploration areas, including new exploration zones, deep strata, and offshore areas. Recent exploration has yielded numerous discoveries, confirming these areas as key areas for breakthroughs, increased reserves, and improved production. In the evaluation and deployment of exploration in these low-exploration zones, the development characteristics of source rocks, especially the presence or absence of effective source rocks reaching the lower limit of organic matter abundance, are the primary issues that need to be addressed in exploration research. Conducting source rock evaluation according to industry standards requires extensive petrochemical analysis data from core samples. However, low-exploration areas have limited well data and lack relevant testing data, making it difficult to meet the data requirements for source rock evaluation.

[0004] Previous researchers have proposed using well logging data to predict organic matter abundance, but this still requires the support of drilling core sampling and well logging data. Some scholars have proposed the relationship between factors such as paleowater depth and systems tract and source rock quality, but most of these are qualitative or semi-quantitative predictions and are not applicable to specific evaluation and prediction.

[0005] Therefore, it is urgent to establish a method for predicting the organic matter abundance of mudstone and shale in low-exploration areas, to provide support for the evaluation of source rocks in low-exploration areas, and to lay the foundation for the evaluation of oil and gas potential in the region.

[0006] Chinese patent application CN201811511167.9 discloses a method and apparatus for predicting the organic matter abundance of source rocks. The method includes: acquiring well logging curves for a target area; calculating the total organic carbon (TOC) value of the target area based on the well logging curves; synthesizing seismic records based on the TOC value of the target area and the well logging curves, and performing well-seismic calibration; extracting seismic attribute features from the wellbore sidetracks based on the well-seismic calibration results, and establishing a relationship between TOC and the seismic attribute features; and establishing the spatial distribution of TOC in the target area based on the relationship.

[0007] Chinese patent application CN201410727185.6 discloses a method and apparatus for predicting adsorbed gas content in shale. The method establishes a first relationship between the Ranyl volume VL of shale samples collected in the study area at different temperatures T, temperature T, and the organic matter abundance (TOC) of the shale samples. It also establishes a second relationship between the logarithm of the Ranyl pressure PL of each shale sample at different temperatures T and the reciprocal of the temperature T. Substituting the first and second relationships into the Ranyl equation yields a third relationship between temperature T, pressure P, the organic matter abundance (TOC) of the shale samples, and the adsorbed gas content (V). Finally, based on the third relationship, the adsorbed gas content (V) of the study area is predicted.

[0008] Chinese patent application CN201910405762.2 discloses a method for predicting the maturity of organic matter in source rocks under overpressure conditions. This method includes: Step 1, collecting immature and low-maturity high-abundance well cores and field samples; Step 2, conducting high-temperature and high-pressure simulation experiments on actual geological samples to obtain laboratory test data; Step 3, analyzing the laboratory data of the cores to obtain conversion rate parameters of the samples at different thermal evolution degrees; Step 4, using the least squares method to obtain the coefficients of the thermal evolution degree calculation formula for the actual block; Step 5, predicting the pressure coefficient based on seismic data and well measurement data of oil and gas basins; and Step 6, predicting the planar distribution characteristics of the organic matter thermal evolution degree under overpressure conditions.

[0009] The existing technologies described above are quite different from the present invention and have failed to solve the technical problem we want to solve. Therefore, we have invented a new method for predicting the organic matter abundance of mudstone and shale in low-exploration areas. Summary of the Invention

[0010] The purpose of this invention is to provide a method for predicting the organic matter abundance of mudstone and shale in low-exploration areas, providing technical support for predicting the distribution of high-quality mudstone and shale and evaluating the oil and gas potential of the zone.

[0011] The objective of this invention can be achieved through the following technical measures: a method for predicting the organic matter abundance of mudstone and shale in areas with low exploration levels, the method comprising:

[0012] Step 1: Determine the distribution of stratigraphic systems and sedimentary centers in each region;

[0013] Step 2: Conduct geochemical analysis and testing related to sedimentary rock facies, elements, and organic matter abundance;

[0014] Step 3: Establish a model for the variation of deposition rate at different sample points;

[0015] Step 4: Establish paleoproductivity change models for each sample point;

[0016] Step 5: Evaluate the redox variation model for each sample point;

[0017] Step 6: Establish correlation models between various sedimentary environmental indicators and organic matter abundance;

[0018] Step 7: Establish a quantitative prediction model for multi-factor organic matter abundance applicable to the study area;

[0019] Step 8: Predict the planar distribution of organic matter abundance.

[0020] The objective of this invention can also be achieved through the following technical measures:

[0021] In step 1, based on a comprehensive study of drilling, outcrops and seismic data in the study area, the distribution of strata in each region is determined; and the sedimentary center and extent are determined by the variation in stratum thickness and sedimentary facies lithology.

[0022] In step 2, for potential mudstone and shale formations, exploratory wells and outcrop samples from the basin margins are used to study sedimentary lithofacies. For mudstone development sections, intensive sampling is conducted to determine the major, trace, and rare earth elements such as calcium (Ca), iron (Fe), boron (B), barium (Ba), strontium (Sr), manganese (Mn), vanadium (V), nickel (Ni), titanium (Ti), chromium (Cr), gallium (Ga), lanthanum (La), ytterbium (Yb), cerium (Ce), and europium (Eu). At the same time, geochemical analysis tests related to the abundance of organic matter are performed.

[0023] In step 3, based on drilling and outcrop testing, a sedimentation rate variation model for different sample points is established using formation thickness, sedimentary age, and elemental indices such as La and Yb.

[0024] In step 4, the paleoproductivity change model for each sample point is established using the results of elemental measurements of Ba and Al.

[0025] In step 5, the redox variation model of each sample point is evaluated using elemental indices such as B-Ga and V-Ni.

[0026] In step 6, a correlation model between various sedimentary environmental indicators and organic matter abundance is established. The relationship between organic matter abundance and parameters such as sedimentation rate, paleoproductivity, and redox degree is analyzed using single-factor analysis, and the single-factor relationship formula is regressed.

[0027] In step 6, the formula for the relationship between single elements is:

[0028] TOC1=f(P 古生产力 )

[0029] TOC2=f(I 沉积速率 )

[0030] TOC3=f(I还原 )

[0031] TOC, or organic carbon content, refers to the percentage of the total carbon content of all organic matter in a rock by its total weight, expressed as %.

[0032] P 古生产力 Paleoproductivity refers to the rate at which organisms fix energy during energy cycles in geological history; that is, the amount of organic matter produced per unit area per unit time, expressed in g / (m²). 2 a);

[0033] Deposition rate refers to the thickness of the strata deposited per unit deposition time, and its unit is usually cm / ka; the I in this formula 沉积速率 It refers to a dimensionless parameter that reflects the ratio of sedimentation rates during a geological period, obtained by using the content of elements such as Fe, Mn, La, and Yb. The higher the parameter, the greater the sedimentation rate.

[0034] Redox conditions refer to the concentration of oxygen in water, which can be classified into oxidizing, anoxic, and hypoxic conditions. Many elements undergo activation and migration under oxidizing conditions, while precipitating under reducing conditions. The I in the formula... 还原 It refers to a dimensionless ratio parameter that reflects the redox conditions of water bodies, obtained by utilizing the content of elements such as V, Ni, Th, and U.

[0035] In step 7, a quantitative prediction model for the abundance of multi-factor organic matter in the study area is established using multi-factor regression.

[0036] In step 7, the following formula is based on P 古生产力 I 沉积速率 I 还原 The TOC calculation formula derived from fitting three parameters varies across different regions.

[0037] TOC = f(P) 古生产力 I 沉积速率 I 还原 )

[0038] TOC stands for organic carbon content, expressed as a percentage (%). 古生产力 This refers to the paleoproductivity value, that is, the amount of organic matter produced per unit area per unit time, with units of g / (m²). 2 a);I 沉积速率 This refers to a dimensionless ratio parameter, obtained by utilizing the elemental contents of Fe, Mn, La, and Yb, reflecting the sedimentation rate within a specific geological period; I 还原 It refers to a dimensionless ratio parameter that reflects the redox conditions of water bodies, obtained by utilizing the content of elements such as V, Ni, Th, and U.

[0039] In step 8, the planar distribution of organic matter abundance is predicted by using the measured TOC of the sample as a constraint and combining the understanding of sedimentary phase distribution.

[0040] The method for predicting the organic matter abundance of mudstone and shale in low-exploration areas in this invention, based on seismic data, proposes to establish a quantitative relationship between elemental sedimentary parameters and total organic carbon (TOC) index by analyzing and testing samples from outcrops at the basin margin and typical exploratory wells, and predicts the distribution of organic matter abundance.

[0041] The innovations of this invention are as follows: First, based on the lack of well data in low-exploration areas, and using outcrop sampling test results as a basis and individual well sample test data as constraints, an innovative prediction method that does not rely on well logging and seismic data is proposed; Second, the method takes the organic matter deposition and enrichment mechanism as its core, and starts from the quantitative evaluation of the water sedimentation environment, and innovatively establishes a multi-parameter fitting quantitative prediction model for organic matter abundance.

[0042] The organic matter abundance distribution prediction method in this invention involves theoretical methods from sedimentology, elemental geochemistry, and organic geochemistry, aiming to provide technical support and theoretical basis for predicting organic matter abundance in low-exploration areas. Based on systematic core sampling, seismic data, and analytical testing data, a multi-element parameter fitting method for predicting organic matter abundance distribution was established for the first time. This invention solves the problem of difficult prediction of organic matter distribution in source rocks of terrestrial sedimentary environments, improves the accuracy of mudstone and shale quality prediction, and lays a solid theoretical foundation for the evaluation of source rocks in terrestrial lacustrine basins, the distribution patterns of oil and gas, and the exploration and development of shale oil and gas. Attached Figure Description

[0043] Figure 1 This is a flowchart of a specific embodiment of the method for predicting the organic matter abundance of mudstone and shale in low-exploration areas according to the present invention;

[0044] Figure 2 This is a distribution map of the P2l sedimentary facies in the southeastern region of the present invention, as shown in a specific embodiment.

[0045] Figure 3 This is a schematic diagram of the P2l mudstone shale elemental geochemical composite profile of the Zhundongnan Hongyanchi section in a specific embodiment of the present invention.

[0046] Figure 4 This is a graph showing the relationship between P2l settling rate elemental indices and TOC in the southeastern region of the present invention, in a specific embodiment of the present invention.

[0047] Figure 5 This is a diagram showing the relationship between the P2l paleoproductivity index and TOC in the Quasi-Southeast region in a specific embodiment of the present invention;

[0048] Figure 6This is a diagram showing the relationship between the oxidation-reduction index of P2l water and TOC in a specific embodiment of the present invention;

[0049] Figure 7 This is a distribution map of P2l organic matter abundance in the southeastern region of the present invention (unit: %). Detailed Implementation

[0050] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0051] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, and / or combinations thereof.

[0052] like Figure 1 As shown, Figure 1 This is a flowchart of the method for predicting the organic matter abundance of mudstone and shale in low-exploration areas according to the present invention.

[0053] Step 1: Based on a comprehensive study of drilling, outcrop, and seismic data in the study area, determine the distribution of strata in each region; determine the sedimentary center and extent by analyzing the variations in strata thickness and sedimentary facies lithology.

[0054] Step 2: For potential shale and mudstone formations, conduct exploratory well and outcrop sample sedimentary lithofacies studies; for mudstone development intervals, intensively sample and determine major, trace and rare earth elements such as calcium (Ca), iron (Fe), boron (B), barium (Ba), strontium (Sr), manganese (Mn), vanadium (V), nickel (Ni), titanium (Ti), chromium (Cr), gallium (Ga), lanthanum (La), ytterbium (Yb), cerium (Ce), europium (Eu), etc., and at the same time conduct geochemical analysis tests related to organic matter abundance.

[0055] Step 3: Based on drilling and outcrop testing, establish a sedimentation rate variation model for different sample points using formation thickness, sedimentary age, and elemental indices such as La and Yb.

[0056] Step 4: Using the results of elemental determinations such as Ba and Al, establish a paleoproductivity change model for each sample point.

[0057] Step 5: Use elemental indices such as B-Ga and V-Ni to evaluate the redox variation model of each sample point.

[0058] Step 6: Establish correlation models between various sedimentary environmental indicators and total organic matter (TOC), perform single-factor analysis on the relationship between organic matter abundance and parameters such as sedimentation rate, paleoproductivity, and redox degree, and regress the single-factor relationship formula.

[0059] TOC1=f(P 古生产力 )

[0060] TOC2=f(I 沉积速率 )

[0061] TOC3=f(I 还原 )

[0062] Step 7: Utilize multifactor regression and other methods to establish a quantitative prediction model for the abundance of multifactor organic matter in the study area.

[0063] TOC = f(P) 古生产力 I 沉积速率 I 还原 ,...)

[0064] Step 8: Using the measured TOC of the sample as a constraint and combined with the understanding of sedimentary facies distribution, predict the planar distribution of organic matter abundance.

[0065] The following are several specific embodiments of the application of the present invention.

[0066] Example 1:

[0067] In a specific embodiment 1 of the present invention, a block with medium to low exploration levels, such as the periphery of the Bogda Mountains in the southeast of the Junggar Basin, was selected as the study area. The study stratum is the Middle Permian Lucaogou Formation (P2l). Drilling in the study area is sparsely distributed in the piedmont structural zone, revealing relatively few P2l source rocks; the outcrops are well exposed, facilitating sampling and analysis. The specific method is as follows:

[0068] (1) Using drilling, outcrop and seismic data, the P2l layer in the study area was marked, and then the stratigraphic distribution in the study area was clarified by lateral tracing and stratigraphic boundaries were determined.

[0069] (2) Based on the comprehensive analysis of sedimentary facies characteristics such as lithology, grain size, roundness, color, and rock composition, and the results of outcrop and well element analysis, the original sedimentary center and extent are predicted. Figure 2 ).

[0070] (3) Systematic sampling (sample interval 0.5m-5m) will be conducted on existing core samples and the P2l section of the field geological profile. For key sections, the sampling interval can be increased (e.g., 0.2m-0.5m). Major, trace, and rare earth elements such as Ca, Fe, B, Ba, Sr, Mn, V, Ni, Ti, Cr, Ga, La, Yb, Ce, and Eu will be determined. Based on the results, key element parameters such as Fe / Mn, V / Ni, Sr / Ba, and La / Yb will be analyzed, and a comprehensive geochemical profile will be compiled. Figure 3 ).

[0071] (4) Based on the test results of field systematic sampling, correlation analysis was conducted between elemental indices reflecting sedimentation rate, such as Fe / Mn, Mn / Ti, La / Yb, and Co / Ti, and TOC. The results showed a significant negative correlation between sedimentation rate and organic matter abundance; that is, the slower the sedimentation rate, the higher the organic matter abundance. Based on this, a sedimentation rate elemental parameter (Ig) was established. 沉积速率 The quantitative relationship between () and TOC Figure 4 ).

[0072] TOC1 = 6.2683 × e -1.035(La / Yb) (R 2 =0.705)

[0073] (5) Using sedimentation rate (Rs) and sediment dry weight (P) DB ) Calculate the mass accumulation rate (R) Ma Using the test results of elements such as Ba and Al, the relationship between terrestrial barium, biogenic barium, and paleoproductivity (P) was calculated. 古生产力 The ancient productivity calculation process is as follows:

[0074] Ba 陆源 =Al × 0.0075

[0075] Ba 生源 =Ba-Ba 陆源

[0076] R Ma =Rs×P DB

[0077] Ba 理论生源 =Ba 生源 / (0.209LgR MA -0.213)+

[0078] P = 0.195 × (Ba 理论生源 ) 1.41

[0079] A correlation diagram between ancient productivity and TOC was constructed, showing a good positive correlation between the two, thus establishing a quantitative relationship between ancient productivity and TOC. Figure 5 ).

[0080] TOC2 = 0.0047 × P + 0.599 (R) 2 =0.681)

[0081] (6) Using elemental parameters such as U / Th and V / Ni to reflect the redox environment of deposition (I 还原 ), analyze the correlation with TOC, and establish a quantitative relationship between key redox parameters and TOC (). Figure 6 ).

[0082] TOC3=18.123×(U / Th)-5.0248(R 2 =0.667)

[0083] (7) Based on the aforementioned quantitative relationship formula, a multivariate regression quantitative evaluation model for sedimentation rate, redox environment, paleoproductivity and TOC is established.

[0084] TOC = f(P) 古生产力 I 沉积速率 I 还原 )

[0085] Through multiple regression, a quantitative prediction formula for total organic matter (TOC) under multiple constraints is obtained:

[0086] TOC = 1.09 × e I沉积速率 +0.001×P 古生产力 +21.03×I 还原 -8.81(R 2 =0.872)

[0087] (8) Based on the sedimentary facies distribution, combined with the analysis of actual outcrops and individual well samples' settling rates, redox degrees, and paleoproductivity, and constrained by the measured TOC of the samples, the planar distribution of organic matter abundance can be predicted. Figure 7 ).

[0088] Example 2:

[0089] In a specific embodiment 2 of the present invention, a block with medium to low exploration levels, such as the northeastern edge of the Qaidam Basin, was selected as the study area, and the study stratum was the Lower Carboniferous Huaitoutala Formation. Drilling in the study area was sporadic; the Carboniferous strata were well exposed in sections such as Chengqianggou, Dulanguan Jiaoyahe, and Shihuigou, facilitating sampling and analysis. The specific method is as follows:

[0090] (1) Using drilling, outcrop and seismic data, the C1h stratum in the study area was marked, and then the strata were traced laterally to clarify the distribution of the target strata in the study area and determine the stratigraphic boundaries.

[0091] (2) Based on the comprehensive analysis of sedimentary facies characteristics such as lithology, grain size, roundness, color and rock composition, and the results of outcrop and well element analysis, the sedimentary center and distribution range are predicted.

[0092] (3) Systematic sampling (sample interval 0.5m-5m) was conducted on existing core samples and C1h sections of field geological profiles. For key mudstone and shale sections, the sampling interval was increased to 0.2m to determine major, trace, and rare earth elements. Based on the measurement results, the parameters of key elements such as Fe / Mn, V / Ni, Sr / Ba, and La / Yb were analyzed to compile a comprehensive geochemical profile.

[0093] (4) Based on the test results of drilling and field system sampling, the sedimentation rate of drilling samples was calculated using sedimentation time and formation thickness. Correlation analysis was performed using elemental indices reflecting sedimentation rate, such as Fe / Mn, Mn / Ti, Lan / Ybn, and Co / Ti, with TOC. A significant negative correlation was found between TOC and organic matter abundance; that is, the slower the sedimentation rate, the higher the organic matter abundance. Based on this, a sedimentation rate elemental parameter (Ig) was established. 沉积速率 The quantitative relationship between () and TOC.

[0094] TOC1 = 7.1153 × e -0.7984×I沉积速率 (R 2 =0.785)

[0095] (5) Using sedimentation rate (Rs) and sediment dry weight (P) DB ) Calculate the mass accumulation rate (R) Ma Using the test results of elements such as Ba and Al, the relationship between terrestrial barium, biogenic barium, and paleoproductivity (P) was calculated. 古生产力 ).

[0096] The ancient productivity calculation process is as follows:

[0097] Ba 陆源 =Al × 0.0075

[0098] Ba 生源 =Ba-Ba 陆源

[0099] R Ma =Rs×P DB

[0100] Ba 理论生源 =Ba 生源 / (0.209LgR MA -0.213)+

[0101] P = 0.195 × (Ba 理论生源 ) 1.41

[0102] A correlation diagram between ancient productivity and TOC was constructed, showing a good positive correlation between the two, thus establishing a quantitative relationship between ancient productivity and TOC.

[0103] TOC2 = 0.0108 × P + 0.207 (R) 2 =0.722)

[0104] (6) Using elemental parameters such as V / Ni that reflect the redox environment of deposition (I 还原 We analyzed the correlation between V / Ni index and TOC, and established a quantitative relationship between key redox parameters and TOC.

[0105] TOC3 = 9.5251 × I 还原 -3.0581 (R 2 =0.793)

[0106] (7) Based on the aforementioned quantitative relationship formula, a multivariate regression quantitative evaluation model for sedimentation rate, redox environment, paleoproductivity and TOC is established.

[0107] TOC = f(P) 古生产力 I 沉积速率 I 还原 )

[0108] Through multiple regression, a quantitative prediction formula for total organic matter (TOC) under multiple constraints is obtained:

[0109] TOC = 1.75 × e I沉积速率 +0.028×P 古生产力 +19.66×I 还原 -4.54 (R 2 =0.829)

[0110] (8) Based on the distribution of sedimentary facies, combined with the analysis of actual outcrops and individual well samples of sedimentation rate, redox degree and paleoproductivity, the planar distribution of organic matter abundance in the Huaitoutala Formation of Carboniferous in the northeastern margin of the Qaidam Basin is predicted with the measured TOC of the samples as a constraint.

[0111] Example 3:

[0112] In a specific embodiment 3 of the present invention, a block with medium to low exploration levels, such as the western edge of the Turpan-Hami Basin, was selected as the study area, and the study stratum was the Middle Permian Yaomoshan Formation. Drilling in the study area was sporadic; however, the Permian strata were well exposed in sections such as Aiweiergou, facilitating sampling and analysis. The specific method is as follows:

[0113] (1) Using drilling, outcrop and seismic data, the P2y layer in the study area was marked, and then the layer was traced laterally to clarify the distribution of the target layer in the study area and determine the stratigraphic boundary.

[0114] (2) Based on the comprehensive analysis of sedimentary facies characteristics such as lithology, grain size, roundness, color and rock composition, and the results of outcrop and well element analysis, the sedimentary center and distribution range are predicted.

[0115] (3) Systematic sampling (sample interval 0.5m-5m) was conducted on existing core samples and P2y sections of field geological profiles. For key sections, the sampling interval was increased to 0.5m to determine major, trace, and rare earth elements. Based on the measurement results, the parameters of key elements such as Fe / Mn, V / Ni, Sr / Ba, and La / Yb were analyzed to compile a comprehensive geochemical profile.

[0116] (4) Based on the test results of systematic field sampling, the correlation analysis between the Co / Ti elemental index reflecting the sedimentation rate and TOC was performed. A significant negative correlation was found between TOC and organic matter abundance; that is, the slower the sedimentation rate, the higher the organic matter abundance. Based on this, a sedimentation rate elemental parameter (Ig) was established. 沉积速率 The quantitative relationship between () and TOC.

[0117] TOC1 = 13.1183 × e 1.577×I沉积速率 (R 2 =0.655)

[0118] (5) Using sedimentation rate (Rs) and sediment dry weight (P) DB ) Calculate the mass accumulation rate (R) Ma Using the test results of elements such as Ba and Al, the relationship between terrestrial barium, biogenic barium, and paleoproductivity (P) was calculated. 古生产力 The ancient productivity calculation process is the same as in Example 1, establishing a quantitative relationship between ancient productivity and TOC.

[0119] TOC2 = 0.0073 × P + 0.416 (R) 2 =0.759)

[0120] (6) Using elemental parameters such as V / Ni that reflect the redox environment of deposition (I 还原 We analyzed the correlation between V / Ni index and TOC, and established a quantitative relationship between key redox parameters and TOC.

[0121] TOC3 = 6.7521 × I 还原 -5.6694 (R 2 =0.702)

[0122] (7) Based on the aforementioned quantitative relationship formula, a multivariate regression quantitative evaluation model for sedimentation rate, redox environment, paleoproductivity and TOC is established.

[0123] TOC = f(P) 古生产力 I 沉积速率 I 还原 )

[0124] Through multiple regression, a quantitative prediction formula for total organic matter (TOC) under multiple constraints is obtained:

[0125] TOC = 3.274 × e I沉积速率 +0.017×P 古生产力 +33.529×I 还原 -6.055(R 2 =0.813)

[0126] (8) Based on the distribution of sedimentary facies, combined with the analysis of actual outcrops and individual well samples of sedimentation rate, redox degree and paleoproductivity, the planar distribution of organic matter abundance in the Yaomoshan Formation of the Permian in the Turpan-Hami Basin is predicted with the measured TOC of the samples as a constraint.

[0127] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0128] Except for the technical features described in the specification, all other technologies are known to those skilled in the art.

Claims

1. A method for predicting the organic matter abundance of mudstone and shale in low-exploration areas, characterized in that, Methods for predicting the organic matter abundance of mudstone and shale in low-exploration areas include: Step 1: Determine the distribution of stratigraphic systems and sedimentary centers in each region; Step 2: Conduct geochemical analysis and testing related to sedimentary rock facies, elements, and organic matter abundance; Step 3: Establish a model for the variation of deposition rate at different sample points; Step 4: Establish paleoproductivity change models for each sample point; Step 5: Evaluate the redox variation model for each sample point; Step 6: Establish correlation models between various sedimentary environmental indicators and organic matter abundance; Step 7: Establish a quantitative prediction model for multi-factor organic matter abundance applicable to the study area; Step 8: Predict the planar distribution of organic matter abundance; In step 3, based on drilling and outcrop testing, a sedimentation rate variation model for different sample points is established using formation thickness, sedimentary age, and elemental indices such as La and Yb. In step 6, a correlation model between various sedimentary environment indicators and organic matter abundance is established. The relationship between organic matter abundance and parameters such as sedimentation rate, paleoproductivity, and redox degree is analyzed using single-factor analysis, and the single-factor relationship formula is regressed. In step 7, a quantitative prediction model for the abundance of multi-factor organic matter in the study area is established using multi-factor regression.

2. The method for predicting the organic matter abundance of mudstone and shale in low-exploration areas according to claim 1, characterized in that, In step 1, based on a comprehensive study of drilling, outcrops and seismic data in the study area, the distribution of strata in each region is determined; and the sedimentary center and extent are determined by the variation in stratum thickness and sedimentary facies lithology.

3. The method for predicting the organic matter abundance of mudstone and shale in low-exploration areas according to claim 1, characterized in that, In step 2, for potential mudstone and shale formations, exploratory wells and outcrop samples from the basin margins are used to study sedimentary lithofacies. For mudstone development sections, intensive sampling is conducted to determine the major, trace, and rare earth elements such as calcium (Ca), iron (Fe), boron (B), barium (Ba), strontium (Sr), manganese (Mn), vanadium (V), nickel (Ni), titanium (Ti), chromium (Cr), gallium (Ga), lanthanum (La), ytterbium (Yb), cerium (Ce), and europium (Eu). At the same time, geochemical analysis tests related to the abundance of organic matter are performed.

4. The method for predicting the organic matter abundance of mudstone and shale in low-exploration areas according to claim 1, characterized in that, In step 4, the paleoproductivity change model for each sample point is established using the results of elemental measurements of Ba and Al.

5. The method for predicting the organic matter abundance of mudstone and shale in low-exploration areas according to claim 1, characterized in that, In step 5, the redox variation model of each sample point is evaluated using elemental indices such as B-Ga and V-Ni.

6. The method for predicting the organic matter abundance of mudstone and shale in low-exploration areas according to claim 1, characterized in that, In step 6, the formula for the relationship between single elements is: TOC1=f(P 古生产力 ) TOC2=f(I 沉积速率 ) TOC3=f(I 还原 ) TOC, or organic carbon content, refers to the percentage of total carbon in all organic matter of a rock by its total weight, expressed as a percentage (%). P 古生产力 Paleoproductivity refers to the rate at which organisms fix energy during energy cycles in geological history; that is, the amount of organic matter produced per unit area per unit time, expressed in g / (m²). 2 a) Deposition rate refers to the thickness of the strata deposited per unit deposition time, and its unit is usually cm / ka; the I in this formula 沉积速率 It refers to a dimensionless parameter that reflects the ratio of sedimentation rates during a geological period, obtained by using the content of elements such as Fe, Mn, La, and Yb. The higher the parameter, the greater the sedimentation rate. Redox conditions refer to the concentration of oxygen in water, which can be classified into oxidizing, anoxic, and hypoxic conditions. Many elements undergo activation and migration under oxidizing conditions, while precipitating under reducing conditions. The I in the formula... 还原 It refers to a dimensionless ratio parameter that reflects the redox conditions of water bodies, obtained by utilizing the content of elements such as V, Ni, Th, and U.

7. The method for predicting the organic matter abundance of mudstone and shale in low-exploration areas according to claim 1, characterized in that, In step 7, the following formula is based on P 古生产力 I 沉积速率 I 还原 The TOC calculation formula derived from fitting three parameters varies across different regions. TOC=f(P 古生产力 ,I 沉积速率 ,I 还原 ) TOC stands for organic carbon content, and its unit is %; P 古生产力 This refers to the paleoproductivity value, that is, the amount of organic matter produced per unit area per unit time, with units of g / (m²). 2 a); I 沉积速率 This refers to a dimensionless ratio parameter, obtained by utilizing the elemental contents of Fe, Mn, La, and Yb, reflecting the sedimentation rate within a specific geological period; I 还原 It refers to a dimensionless ratio parameter that reflects the redox conditions of water bodies, obtained by utilizing the content of elements such as V, Ni, Th, and U.

8. The method for predicting the organic matter abundance of mudstone and shale in low-exploration areas according to claim 1, characterized in that, In step 8, the planar distribution of organic matter abundance is predicted by using the measured TOC of the sample as a constraint and combining the understanding of sedimentary phase distribution.

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