High-siliceous shale longitudinal sweet spot prediction method

Abstract

The invention provides a high-siliceous shale longitudinal dessert prediction method which comprises the following steps: S1, collecting a shale core sample, and obtaining actual measurement experiment data and logging data of shale; wherein the actual measurement experiment data of the shale comprises actual measurement TOC, nuclear magnetic porosity and siliceous mineral relative content; s2, establishing a relationship among the actually measured TOC, the nuclear magnetic porosity and the relative content of the siliceous minerals, and determining the lower limit values of the relative content of the siliceous minerals, the TOC and the nuclear magnetic porosity of the gas production section; s3, establishing a logging siliceous mineral relative content calculation model; s4, determining a shale dessert section; and S5, verifying the accuracy of the shale dessert section. The method takes the relative content of siliceous minerals as a key parameter, and is simple and clear; the relative content of the siliceous minerals is also the most important brittle minerals in the shale, the higher the relative content of the siliceous minerals is, the better the brittleness of the shale is, and fracturing is facilitated, so that the high-siliceous-content section is also an engineering dessert section, and the method gives consideration to prediction of geological and engineering double desserts.

Description

Technical Field

[0001] The invention belongs to the technical field of petroleum exploration and development, and in particular relates to a method for predicting a vertical sweet spot in high-siliceous shale. Background Art

[0002] Shale is usually used as a source rock. The higher the abundance of organic matter, the greater the amount of oil and gas generated. At the same time, shale also has certain storage properties, so the shale sweet spot must have a relatively high total organic carbon content (TOC) value and a degree of pore development. At the same time, considering the need for later fracturing, it must also have a high brittleness. Brittle minerals mainly include siliceous minerals (quartz) and carbonate rock minerals.

[0003] The shale gas "sweet spot" refers to the best area or layer for shale gas exploration and development. Its typical characteristics are: thick shale (greater than 30m), in the "gas window", high TOC, high content of brittle minerals such as quartz (strong compressibility), low montmorillonite content, overpressure, abnormal gas logging, adjacent to conventional oil and gas reservoirs, good surface conditions, etc. At present, the method of predicting shale gas geological sweet spots mainly determines and predicts shale gas geological sweet spots through instrument well measurements and seismic multi-attribute inversion.

[0004] Existing solutions, such as the invention patent with the publication (announcement) number: CN104749651A, provide a method for quantitatively identifying shale sweet spots by phase-controlled multi-level reconstruction logging. The method includes finely dividing different lithofacies of shale, clarifying the logging response characteristics of various lithofacies, and establishing a quantitative identification model for sweet spots in different lithofacies of shale through multi-level reconstruction fusion of logging under phase control constraints. This method realizes the quantitative identification of shale sweet spots, but mainly carries out identification from the perspective of lithofacies, and does not start from key parameters such as shale source and reservoir conditions and fracturing.

[0005] The invention patent with the publication (announcement) number: CN112922591A provides a method and system for predicting the "sweet spot" of shale reservoir lithofacies. The method obtains the attribute parameters of the relevant mineral content based on the intersection relationship between the attribute parameters of the shale reservoir lithofacies and the daily oil production per meter, builds a prediction model based on the obtained parameters, and comprehensively judges the "sweet spot" based on the model and the daily oil production per meter. This method comprehensively considers multiple parameters of shale, but does not use logging methods to carry out predictions, so it is insufficient in its wide applicability. Summary of the invention

[0006] The present invention aims to provide a method for predicting vertical sweet spots in high-siliceous shale to solve the problems of selecting sections for shale oil and gas exploration wells and selecting targets for horizontal wells, thereby improving the drilling rate of gas layers in horizontal sections and increasing the production of single wells.

[0007] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0008] A method for predicting vertical sweet spots in high-siliceous shale, characterized by comprising the following steps:

[0009] S1, systematically collect shale core samples at certain sampling intervals in the concentrated shale development section, and obtain the measured experimental data and logging data of shale; among which, the measured experimental data of shale include the measured total organic carbon content (TOC), the measured nuclear magnetic porosity and the measured relative content of siliceous minerals;

[0010] S2, establish the relationship between the measured TOC, measured nuclear magnetic porosity and measured relative content of siliceous minerals in the shale development section, determine the lower limit of the relative content of siliceous minerals, TOC and nuclear magnetic porosity in the gas production section, and then clarify the distribution range of the favorable area of ​​shale sweet spots; (keep red and remove shale "oil")

[0011] S3, establishing a calculation model for the relative content of siliceous minerals in well logging according to the well logging data obtained in step S1, and obtaining the relative content of siliceous minerals in well logging;

[0012] S4, determine the shale sweet spot

[0013] The relative content of siliceous minerals calculated by well logging in step S3 is counted, and the data segment whose relative content of siliceous minerals is greater than the lower limit value of the relative content of siliceous minerals measured in step S2 is selected, and the lower limit value of the measured TOC and the lower limit value of the nuclear magnetic porosity obtained in step S2 are combined to determine the vertical sweet spot of the shale;

[0014] S5, verify the accuracy of shale sweet spot segment.

[0015] Furthermore, the shale logging data in step S1 includes shale formation density, neutron porosity, natural gamma and lithology coefficient.

[0016] Furthermore, the step S2 determines the lower limits of the relative content of siliceous minerals, TOC and nuclear magnetic porosity in the gas-producing section, and further clarifies the distribution range of the favorable area of ​​shale oil sweet spots by: obtaining the minimum values ​​of TOC, nuclear magnetic porosity and relative content of siliceous minerals in the gas-producing section according to the scatter plot intersection method, that is, the lower limits of the measured TOC, nuclear magnetic porosity and relative content of siliceous minerals corresponding to the shale sweet spot section; and determining the shale distribution range section exceeding the lower limits of the relative content of siliceous minerals, TOC and nuclear magnetic porosity in the gas-producing section as the favorable area of ​​shale oil sweet spots.

[0017] Preferably, the method for determining the lower limit of the relative content of siliceous minerals, TOC and nuclear magnetic porosity in the gas-producing section in step S2 is:

[0018] First, the TOC lower limit corresponding to industrial production capacity is determined based on the cross-plot of measured TOC value and single well production;

[0019] Then, according to the cross plot of the measured TOC value and the measured relative content of siliceous minerals, the relative content of siliceous minerals corresponding to the lower limit of TOC is determined as the lower limit of the relative content of siliceous minerals in the gas-producing section;

[0020] Finally, according to the cross plot of the measured relative content of siliceous minerals and the measured nuclear magnetic porosity, the nuclear magnetic porosity corresponding to the lower limit of the relative content of siliceous minerals is determined as the lower limit of the nuclear magnetic porosity content in the gas-producing section.

[0021] Furthermore, the S3 establishes a calculation model for the relative content of siliceous minerals in well logging, comprising the following steps:

[0022] S301, calculate the total mud content sh, the specific method is:

[0023] First, calculate the relative value of natural gamma based on the natural gamma value measured by well logging, and then find the total mud content in the formation;

[0024] S302, establishing a set of equations based on the logging data obtained in step S1, and solving the set of equations to obtain the relative content of each mineral, and then obtaining the relative content of siliceous minerals in the shale.

[0025] Furthermore, the calculation formula of the relative value of natural gamma in step S301 is ΔGR=(GR-GR min ) / (GR max -GR min );

[0026] Where, GR: natural gamma value measured by well logging;

[0027] GR min : minimum value of natural gamma in shale section;

[0028] GR max : Maximum value of natural gamma in shale section.

[0029] Furthermore, the calculation formula for the total mud content in the formation in step S301 is:

[0030]

[0031] Where: GR: natural gamma value measured by well logging;

[0032] GCUR: Hilch index, an empirical index with a value of 2 for old strata and 3.7 for new strata.

[0033] Furthermore, the equation group in step S302 is:

[0034] Where: a, b, c, d are unknown values, representing the illite content, the relative content of siliceous minerals, the calcite content, and the dolomite content, respectively;

[0035] ρ α : shale formation density measured by well logging;

[0036] ρ illte : Illite density characteristic value, generally 2.53 (g / cm 3 );

[0037] The characteristic value of quartz density is generally 2.65 (g / cm 3 );

[0038] ρ lime : Calcite density characteristic value, generally taken as 2.71 (g / cm 3 );

[0039] ρ dolo : The characteristic value of dolomite density is generally 2.87 (g / cm 3 );

[0040] φ cnl : shale neutron porosity measured by well logging;

[0041] φ illte : Porosity characteristic value of illite, generally 21 (pu);

[0042] The characteristic value of quartz porosity is generally 0 (pu);

[0043] φ lime : characteristic value of calcite porosity, generally 0 (pu);

[0044] φ dolo : characteristic value of dolomite porosity, generally 0 (pu);

[0045] P e : shale lithology coefficient measured by well logging;

[0046] The characteristic value of illite lithology coefficient is generally 3.45 (b / e);

[0047] The characteristic value of quartz lithology coefficient is generally 1.81 (b / e);

[0048] The characteristic value of the calcite lithology coefficient is generally taken as 5.08 (b / e);

[0049] The characteristic value of dolomite lithology coefficient is generally 3.14 (b / e).

[0050] Furthermore, in step S5, verifying the accuracy of the shale sweet spot includes:

[0051] S501, comparing the relative content data of siliceous minerals measured in the laboratory in step S1 with the relative content data of siliceous minerals calculated by well logging in step S3 to see whether they are consistent, so as to determine whether the method for calculating the relative content of siliceous minerals is effective;

[0052] S502, comparing the sweet spot calculated by logging in step S4 with the high value area of ​​TOC value and nuclear magnetic porosity (i.e., favorable area of ​​shale sweet spot) obtained in step S2 to see whether they correspond, so as to determine whether the sweet spot segment is accurate.

[0053] Furthermore, in step S1, the logging data is required to correspond one-to-one with the well depth and other data of the collected shale core samples, that is, the logging data at the same depth point and the measured experimental data correspond one-to-one.

[0054] By adopting the above technical solution, the present invention has the following beneficial effects:

[0055] 1. The present invention uses silica content as a key parameter. On the one hand, the relative content of silica minerals is positively correlated with TOC value and porosity, and can be used as a key parameter for whether the source and reservoir conditions are superior; on the other hand, the relative content of silica minerals is also the most important brittle mineral in shale. The higher the relative content of silica minerals, the better the brittleness of the shale, and the more conducive to fracturing. Therefore, the high silica content section is also an engineering sweet spot section. This method takes into account the prediction of both geological and engineering sweet spots.

[0056] 2. In actual production, it is impossible to sample the entire well section of all exploration wells and carry out actual measurement of TOC value, actual NMR porosity and actual relative content of siliceous minerals, etc. However, each exploration well will be logged. This method is based on logging data to predict the distribution range of vertical sweet spots in shale and provide technical support for the next enrichment area.

[0057] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other design solutions and drawings can be obtained based on these drawings without paying creative work.

[0059] Figure 1A flowchart of the steps of a method for predicting a vertical sweet spot in high-siliceous shale provided by an embodiment of the present invention;

[0060] Figure 2 The actual total organic carbon content TOC and the single well production intersection diagram provided by the embodiment of the present invention;

[0061] Figure 3 The actual total organic carbon content TOC and the actual relative content of siliceous minerals provided in the embodiment of the present invention are intersected;

[0062] Figure 4 The intersection diagram of the measured relative content of siliceous minerals and the measured nuclear magnetic porosity provided in the embodiment of the present invention;

[0063] Figure 5 A vertical sweet spot distribution and verification diagram of high-siliceous shale in Well L1 provided in an embodiment of the present invention.

[0064] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments. DETAILED DESCRIPTION

[0065] The content of the present invention can be further understood by combining the following detailed description of the preferred implementation method of the present invention and the embodiments included. Unless otherwise stated, all technical and scientific terms used in this article have the same meaning as those of ordinary skill in the art to which the present invention belongs. If the definition of a specific term disclosed in the prior art is inconsistent with any definition provided in the present invention, the definition of the term provided in the present invention shall prevail.

[0066] The existing technology predicts the vertical sweet spots of shale mainly from the perspective of lithofacies. From the perspective of geological sweet spots, there is no direct correlation with hydrocarbon source conditions (TOC value) and reservoir conditions (porosity). From the perspective of engineering sweet spots, key factors such as brittleness are not considered at all. Figure 1 The present invention provides a method for predicting a vertical sweet spot in high-siliceous shale, comprising the following steps:

[0067] S1, systematically collect shale core samples at certain sampling intervals in the concentrated shale development section, and obtain the measured experimental data and well logging data of shale; among them, the measured experimental data of shale include the measured total organic carbon content (TOC), measured nuclear magnetic porosity and measured relative content of siliceous minerals; the well logging data of shale include shale formation density, neutron porosity, natural gamma and lithology coefficient;

[0068] S2, establish the relationship between the measured TOC, measured NMR porosity and measured relative content of siliceous minerals in the shale sweet spot section, determine the lower limit of the relative content of siliceous minerals, TOC and NMR porosity in the gas-producing section, and then clarify the distribution range of the favorable area of ​​shale sweet spots;

[0069] S3, establishing a calculation model for the relative content of siliceous minerals in well logging according to the well logging data obtained in step S1, and obtaining a distribution curve of the relative content of siliceous minerals in well logging;

[0070] S4, determine the shale sweet spot

[0071] The relative content of siliceous minerals calculated by well logging in step S3 is counted, and the data segment whose relative content of siliceous minerals is greater than the lower limit value of the relative content of siliceous minerals measured in step S2 is selected, and the lower limit value of the measured TOC and the lower limit value of the nuclear magnetic porosity obtained in step S2 are combined to determine the vertical sweet spot of the shale;

[0072] S5, verify the accuracy of shale sweet spot segment.

[0073] Furthermore, the method for clarifying the distribution range of the favorable area of ​​shale oil sweet spots in step S2 is: according to the scatter plot intersection method, the minimum values ​​of TOC, pore development degree and relative content of siliceous minerals in the gas-producing section (i.e., the sweet spot section) are obtained, that is, the lower limits of the measured TOC, measured nuclear magnetic porosity and measured relative content of siliceous minerals corresponding to the shale sweet spot section; the shale distribution range section exceeding the lower limit of the relative content of siliceous minerals in the gas-producing section, the lower limit of TOC and the lower limit of nuclear magnetic porosity is determined as the favorable area of ​​shale oil sweet spots.

[0074] Furthermore, the method for obtaining the lower limit values ​​of the measured TOC, measured nuclear magnetic porosity and measured relative content of siliceous minerals corresponding to the shale sweet spot according to the scatter plot intersection method is as follows:

[0075] First, the TOC lower limit corresponding to industrial production capacity is determined based on the cross-plot of measured TOC value and single well production;

[0076] Then, according to the cross plot of the measured TOC value and the measured relative content of siliceous minerals, the lower limit of the relative content of siliceous minerals in the gas-producing section is determined;

[0077] Finally, the lower limit of the measured porosity content in the gas-producing section is determined based on the cross-plot of the measured relative content of siliceous minerals and the measured porosity.

[0078] Furthermore, step S3 establishes a calculation model for the relative content of siliceous minerals in well logging, including the following steps:

[0079] S301, calculate the total mud content sh, the specific method is:

[0080] First calculate the relative value of natural gamma, then find the total mud content in the formation;

[0081] S302, according to the logging data obtained in step S1, a set of equations is established, and the relative content of each mineral is obtained by solving the set of equations, and then the logging curve distribution of the relative content of siliceous minerals is obtained.

[0082] Furthermore, the calculation formula of the relative value of natural gamma in step S301 is ΔGR=(GR-GR min ) / (GR max -GR min );

[0083] Where, GR: natural gamma value measured by well logging;

[0084] GR min : minimum value of natural gamma in shale section;

[0085] GR max : Maximum value of natural gamma in shale section;

[0086] Furthermore, the calculation formula for the total mud content in the formation is:

[0087]

[0088] Where: GR: natural gamma value measured by well logging;

[0089] GCUR: Hilch index, an empirical index with a value of 2 for old strata and 3.7 for new strata.

[0090] Furthermore, the equation group in step S302 is:

[0091]

[0092] Where: a, b, c, d are unknown values, representing the illite content, the relative content of siliceous minerals, the calcite content, and the dolomite content, respectively;

[0093] ρ α : shale formation density measured by well logging;

[0094] ρ illte : Illite density characteristic value, generally 2.53 (g / cm 3 );

[0095] The characteristic value of quartz density is generally 2.65 (g / cm 3 );

[0096] ρ lime : Calcite density characteristic value, generally taken as 2.71 (g / cm 3 );

[0097] ρ dolo : The characteristic value of dolomite density is generally 2.87 (g / cm 3 );

[0098] φ cnl : shale neutron porosity measured by well logging;

[0099] φ illte : Porosity characteristic value of illite, generally 21 (pu);

[0100] The characteristic value of quartz porosity is generally 0 (pu);

[0101] φ lime : characteristic value of calcite porosity, generally 0 (pu);

[0102] φ dolo : characteristic value of dolomite porosity, generally 0 (pu);

[0103] The shale lithology coefficient measured by well logging;

[0104] The characteristic value of illite lithology coefficient is generally 3.45 (b / e);

[0105] The characteristic value of quartz lithology coefficient is generally 1.81 (b / e);

[0106] The characteristic value of the calcite lithology coefficient is generally taken as 5.08 (b / e);

[0107] The characteristic value of dolomite lithology coefficient is generally 3.14 (b / e).

[0108] Furthermore, in step S5, verifying the accuracy of the shale sweet spot specifically includes:

[0109] S501, comparing the relative content data of siliceous minerals measured in the laboratory in step S1 with the relative content data of siliceous minerals calculated by well logging in step S3 to see whether they are consistent, so as to determine whether the method for calculating the relative content of siliceous minerals is effective;

[0110] S502, comparing the sweet spot segment calculated by logging in step S4 with the distribution range of the favorable area of ​​shale oil sweet spot obtained in step S2 to see whether they correspond, so as to determine whether the sweet spot segment is accurate.

[0111] Compared with the prior art, the present invention uses the relative content of siliceous minerals as a key parameter. On the one hand, the relative content of siliceous minerals is positively correlated with TOC value and porosity, and can be used as a key parameter for determining whether source and reservoir conditions are superior. On the other hand, the relative content of siliceous minerals is also the most important brittle mineral in shale. The higher the relative content of siliceous minerals, the better the brittleness of the shale, and the more conducive it is to fracturing. Therefore, the high siliceous content section is also an engineering sweet spot section. This method takes into account the prediction of both geological and engineering sweet spots.

[0112] The present invention provides a method for predicting the vertical sweet spot of high-siliceous shale, which is specifically implemented by the following steps:

[0113] Step 1: Select a shale gas exploration well (L1 well), which is required to obtain industrial gas flow and carry out full coring work. In the concentrated shale development section, the L1 well shale core samples are systematically collected at a sampling interval of 1.0m. After the collection is completed, the shale core samples are sent to the laboratory for total organic carbon content (TOC), nuclear magnetic resonance and whole rock X-ray diffraction experimental analysis to obtain the measured TOC, measured nuclear magnetic porosity and measured siliceous mineral relative content data of the shale. After that, the core samples collected above are calibrated to the L1 well logging comprehensive column chart according to the depth to obtain the shale density (DEN), neutron porosity (CNL), natural gamma (GR) and lithology coefficient (Pe) at the corresponding depth.

[0114] Special attention should be paid to the requirement that the logging data obtained above should correspond to the well depth and other data of the collected shale core samples, that is, the same depth point should correspond to the DEN, CNL, GR and Pe logging data and the experimental data of TOC, nuclear magnetic porosity and relative content of siliceous minerals, so as to facilitate the subsequent regularity analysis;

[0115] Step 2: Establish the relationship between the measured TOC, measured nuclear magnetic porosity and measured relative content of siliceous minerals in the shale development section, determine the lower limit of the relative content of siliceous minerals, TOC and nuclear magnetic porosity in the gas production section, and further clarify the distribution range of the favorable area of ​​shale oil sweet spots;

[0116] The determination of the lower limit of the measured TOC, measured nuclear magnetic porosity and relative content of siliceous minerals in shale core samples of the gas-producing section of industrial gas flow wells is mainly based on the scatter plot intersection method to obtain the minimum values ​​of TOC, porosity and relative content of siliceous minerals in the gas-producing section (i.e., sweet spot section), which is the lower limit of the measured TOC, measured nuclear magnetic porosity and measured relative content of siliceous minerals corresponding to the shale sweet spot section. The scatter plot intersection is made with the measured relative content of siliceous minerals on the X-axis and the measured TOC or measured nuclear magnetic porosity on the Y-axis, respectively, and it is found that the relative content of siliceous minerals is positively correlated with TOC and porosity, that is, the higher the relative content of siliceous minerals, the higher the TOC and porosity.

[0117] Specifically, the method for determining the lower limit of the relative content of siliceous minerals, TOC and nuclear magnetic porosity in the gas-producing section is:

[0118] First, determine the lower limit of TOC in the gas production section (i.e., sweet spot section), and determine the lower limit of TOC corresponding to industrial production capacity (daily output exceeding 40,000 cubic meters) based on the TOC value and output intersection diagram;

[0119] Then, the lower limit of the relative content of siliceous minerals in the gas production section (i.e., the sweet spot section) is determined, and the relative content of siliceous minerals corresponding to the lower limit of TOC is determined according to the cross-plot between the TOC value and the relative content of siliceous minerals, which is the lower limit of the relative content of siliceous minerals;

[0120] Finally, determine the lower limit of the porosity content in the gas-producing section (i.e., the sweet spot section). According to the cross-plot of the relative content of siliceous minerals and porosity, the porosity corresponding to the lower limit of the relative content of siliceous minerals is the lower limit of the porosity.

[0121] Therefore, the shale distribution section that exceeds the relative content of siliceous minerals, TOC, and porosity is the sweet spot section.

[0122] Step 3: Establish a calculation model for the relative content of siliceous minerals in well logging

[0123] (1) Calculate the total mud content sh

[0124] First calculate the relative value of natural gamma ΔGR = (GR-GR min ) / (GR max -GR min )

[0125] Then calculate the total mud content in the formation

[0126] Note: GR: natural gamma value measured by well logging;

[0127] GR min : minimum value of natural gamma in shale section;

[0128] GR max : Maximum value of natural gamma in shale section;

[0129] GCUR: Hillich index, an empirical index, with a value of 2 for old strata and 3.7 for new strata; the study area is old strata, so the value is 2;

[0130] (2) Solve the equations to obtain the relative content of each mineral, and then obtain the relative content of siliceous minerals in shale b

[0131]

[0132] Note: a, b, c, d are unknown values, representing illite content, relative content of siliceous minerals, calcite content and dolomite content respectively.

[0133] ρ α : shale formation density measured by well logging;

[0134] ρ illte : Illite density characteristic value, generally 2.53 (g / cm 3 );

[0135] The characteristic value of quartz density is generally 2.65 (g / cm 3 );

[0136] ρ lime : Calcite density characteristic value, generally taken as 2.71 (g / cm 3 );

[0137] ρ dolo : The characteristic value of dolomite density is generally 2.87 (g / cm 3 );

[0138] φ cnl : shale neutron porosity measured by well logging;

[0139] φ illte : Porosity characteristic value of illite, generally 21 (pu);

[0140] The characteristic value of quartz porosity is generally 0 (pu);

[0141] φ lime : characteristic value of calcite porosity, generally 0 (pu);

[0142] φ dolo : characteristic value of dolomite porosity, generally 0 (pu);

[0143] The shale lithology coefficient measured by well logging;

[0144] The characteristic value of illite lithology coefficient is generally 3.45 (b / e);

[0145] The characteristic value of quartz lithology coefficient is generally 1.81 (b / e);

[0146] The characteristic value of the calcite lithology coefficient is generally taken as 5.08 (b / e);

[0147] The characteristic value of dolomite lithology coefficient is generally 3.14 (b / e).

[0148] This formula fully considers the logging data that are most closely related to lithology in the three logging series, namely shale density (DEN), neutron porosity (CNL) and lithology coefficient (Pe). Therefore, this formula is effective for calculating the relative content of siliceous minerals. The logging curve distribution of the relative content of siliceous minerals is obtained based on this formula.

[0149] Step 4: Determine the shale sweet spot

[0150] The relative content of siliceous minerals calculated by logging in step 3 is statistically analyzed, and the relative content of siliceous minerals greater than the lower limit value (the data segment determined in step 2) is selected as the shale sweet spot segment.

[0151] Step 5: Verify the accuracy of shale sweet spots

[0152] (1) Compare the relative content data of siliceous minerals measured in the laboratory with the relative content data of siliceous minerals calculated by well logging in step 3 to see whether they are consistent, so as to determine whether the calculation method of the relative content of siliceous minerals is effective;

[0153] (2) Whether the sweet spot calculated by logging in step 4 corresponds to the high value area of ​​TOC value and porosity can be determined to determine whether the sweet spot is accurate.

[0154] The significance of the invention: In actual production, it is impossible to sample the entire well section of all exploration wells and carry out actual measurement of TOC, actual measurement of nuclear magnetic porosity and actual measurement of relative content analysis of siliceous minerals, but each exploration well will be logged. This method is based on logging data to predict the distribution range of vertical sweet spots in shale, providing technical support for the next enrichment area.

[0155] In a specific embodiment:

[0156] The method for predicting the vertical sweet spot of high-siliceous shale in the 4246-4302m well section of Well L1 includes the following steps:

[0157] ① Systematic core sampling was carried out in the well section of 4246-4302m in depth, and the cores were sent to the laboratory for experimental analysis of measured TOC, measured nuclear magnetic porosity and measured relative content of siliceous minerals (the whole text should be unified as relative content of siliceous minerals) to obtain the measured TOC, measured nuclear magnetic porosity and measured relative content of siliceous minerals data;

[0158] ②Use the intersection diagram analysis method to determine the lower limit values ​​of the relative content of siliceous minerals, TOC, and porosity.

[0159] First, determine the lower limit of TOC in the gas production section (i.e., sweet spot section)

[0160] Reference Figure 2According to the intersection diagram of TOC value and output, the TOC lower limit corresponding to industrial capacity (daily output exceeds 40,000 cubic meters) is determined, TOC = 0.6%;

[0161] Then, determine the lower limit of the relative content of siliceous minerals in the gas-producing section (i.e., the sweet spot section)

[0162] Reference Figure 3 According to the cross-plot of TOC value and relative content of siliceous minerals, it is determined that the relative content of siliceous minerals corresponding to TOC = 0.6% is 43%;

[0163] Finally, determine the lower limit of the porosity content in the gas production section (i.e., the sweet spot section)

[0164] Reference Figure 4 According to the intersection diagram of the relative content of siliceous minerals and porosity, the porosity corresponding to the relative content of siliceous minerals being 43% is 3.2%. Therefore, the distribution section of the shale in the 4246-4302m section of Well L1 with a relative content of siliceous minerals >43%, TOC >0.6%, and porosity >3.2% is identified as the sweet spot section.

[0165] ③ Calculate the relative content of siliceous minerals in the L1 well section at a depth of 4246-4302m.

[0166] In order to better demonstrate the effect, the 5 depth points A, B, C, D, and E in the well section of 4246-4302 m were selected for logging to obtain the relative content of siliceous minerals. First, according to the natural GR, the shale content sh corresponding to the 5 depth points A, B, C, D, and E was obtained. Secondly, according to the equation in step 3, the corresponding logging parameters were used to obtain the relative content b of siliceous minerals calculated by logging at the 5 depths A, B, C, D, and E, that is, b 测井A =35.13%, b 测井B =40.25%, b 测井C =34.37%, b 测井D =63.21%, b 测井E =38.76%

[0167] ④ In the L1 well section with a depth of 4246-4302m, the relative content of siliceous minerals, measured TOC, and measured nuclear magnetic porosity were calculated based on well logging. According to their respective lower limits (TOC>0.6%, measured nuclear magnetic porosity>3.2%), as follows: Figure 5 As shown, the shale sweet spot section is divided, that is, the range greater than the lower limit is the shale vertical sweet spot distribution range (4289-4292m).

[0168] ⑤Finally, the predicted shale vertical sweet spot is verified.

[0169] The relative content of silica minerals corresponding to the five depth points A, B, C, D, and E, that is, b 实测A=35.36%, b 实测B =41.53%, b 实测C =34.03%, b 实测D =63.11%, b 实测E =38.65%, and compared with the relative content of siliceous minerals calculated by logging in ③. If the measured results are consistent with the calculated results.

[0170] Through the application of this method in the shale gas exploration of the Uralik Formation in the western Ordos Basin, sweet spot prediction was carried out for four vertical wells, and the fracturing section was implemented, and high-yield industrial gas flow was obtained successively. The sweet spot section was implemented in one horizontal well, with a gas layer drilling rate of 87%. The gas test achieved a high yield of 264,800 cubic meters per day, which greatly increased the single well production.

[0171] In addition, the advantages of the present invention are: (1) It is mainly a method for predicting sweet spots using well logging technology. Well logging is performed on each exploratory well, and data are easy to obtain and have a wide range of applications. (2) The relative content of siliceous minerals is used as the main parameter, which is simple and clear. (3) For high-siliceous shale, both geological sweet spots and engineering sweet spots are taken into account.

[0172] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, without departing from the technical principles of the present invention, these technicians can design many other modifications and implementations, and these modifications and implementations will fall within the scope and spirit of the principles disclosed in this application.

Claims

1. A method for predicting vertical sweet spots in high-siliceous shale, characterized in that: The steps include: S1, systematically collect shale core samples at certain sampling intervals in the concentrated shale development section, and obtain the measured experimental data and logging data of shale; among which, the measured experimental data of shale include measured TOC, measured nuclear magnetic porosity and measured relative content of siliceous minerals; S2, establish the relationship between the measured TOC, measured NMR porosity and measured relative content of siliceous minerals in the shale development section, determine the lower limit of the relative content of siliceous minerals, TOC and NMR porosity in the gas production section, and then clarify the distribution range of the favorable area of ​​shale sweet spots; S3, establishing a calculation model for the relative content of siliceous minerals in well logging according to the well logging data obtained in step S1, and obtaining the relative content of siliceous minerals in well logging; S4, determine the shale sweet spot The relative content of siliceous minerals calculated by well logging in step S3 is counted, and the data segment whose relative content of siliceous minerals is greater than the lower limit value of the relative content of siliceous minerals measured in step S2 is selected, and the lower limit value of the measured TOC and the lower limit value of the nuclear magnetic porosity obtained in step S2 are combined to determine the vertical sweet spot of the shale; S5, verify the accuracy of shale sweet spot segment.

2. The method for predicting vertical sweet spots in high-siliceous shale according to claim 1, characterized in that: The shale logging data in step S1 includes shale formation density, neutron porosity, natural gamma and lithology coefficient.

3. The method for predicting the vertical sweet spot of high-siliceous shale according to claim 1, characterized in that: The method for determining the lower limits of the relative content of siliceous minerals, TOC and nuclear magnetic porosity in the gas-producing section, and further clarifying the distribution range of the favorable area of ​​shale oil sweet spots in step S2 is as follows: obtaining the minimum values ​​of TOC, nuclear magnetic porosity and relative content of siliceous minerals in the gas-producing section according to the scatter plot intersection method, that is, the lower limits of the measured TOC, nuclear magnetic porosity and relative content of siliceous minerals corresponding to the shale sweet spot section; and determining the shale distribution range section exceeding the lower limits of the relative content of siliceous minerals, the lower limits of TOC and the lower limits of nuclear magnetic porosity in the gas-producing section as the favorable area of ​​shale oil sweet spots.

4. The method for predicting the vertical sweet spot of high-siliceous shale according to claim 1 or 3, characterized in that: The method for determining the lower limit of the relative content of siliceous minerals, TOC and nuclear magnetic porosity in the gas-producing section in S2 is: First, the TOC lower limit corresponding to industrial production capacity is determined based on the cross-plot of measured TOC value and single well production; Then, according to the cross plot of the measured TOC value and the measured relative content of siliceous minerals, the relative content of siliceous minerals corresponding to the lower limit of TOC is determined as the lower limit of the relative content of siliceous minerals in the gas-producing section; Finally, according to the cross plot of the measured relative content of siliceous minerals and the measured nuclear magnetic porosity, the nuclear magnetic porosity corresponding to the lower limit of the relative content of siliceous minerals is determined as the lower limit of the nuclear magnetic porosity content in the gas-producing section.

5. The method for predicting the vertical sweet spot of high-siliceous shale according to claim 2, characterized in that: The step S3 establishes a calculation model for the relative content of siliceous minerals in well logging, comprising the following steps: S301, calculate the total mud content sh, the specific method is: First, calculate the relative value of natural gamma based on the natural gamma value measured by well logging, and then find the total mud content in the formation; S302, establishing a set of equations based on the logging data obtained in step S1, and solving the set of equations to obtain the relative content of each mineral, and then obtaining the relative content of siliceous minerals in the shale.

6. The method for predicting the vertical sweet spot of high-siliceous shale according to claim 5, characterized in that: The calculation formula of the relative value of natural gamma in step S301 is ΔGR=(GR-GR min ) / (GR max -GR min ); Where, GR: natural gamma value measured by well logging; GR min : minimum value of natural gamma in shale section; GR max : Maximum value of natural gamma in shale section.

7. The method for predicting the vertical sweet spot of high-siliceous shale according to claim 6, characterized in that: The calculation formula for the total mud content in the formation in step S301 is: Where: GR: natural gamma value measured by well logging; GCUR: Hilch index, an empirical index with a value of 2 for old strata and 3.7 for new strata.

8. The method for predicting the vertical sweet spot of high-siliceous shale according to claim 6, characterized in that: The equation group in step S302 is: Where: a, b, c, d are unknown values, representing the illite content, the relative content of siliceous minerals, the calcite content, and the dolomite content, respectively; ρ α : shale formation density measured by well logging; ρ illte : Illite density characteristic value, generally 2.53 (g / cm 3 ); The characteristic value of quartz density is generally 2.65 (g / cm 3 ); ρ lime : Calcite density characteristic value, generally taken as 2.71 (g / cm 3 ); ρ dolo : The characteristic value of dolomite density is generally 2.87 (g / cm 3 ); φ cnl : shale neutron porosity measured by well logging; φ illte : Porosity characteristic value of illite, generally 21 (pu); The characteristic value of quartz porosity is generally 0 (pu); φ lime : characteristic value of calcite porosity, generally 0 (pu); φ dolo : characteristic value of dolomite porosity, generally 0 (pu); P e : shale lithology coefficient measured by well logging; The characteristic value of illite lithology coefficient is generally 3.45 (b / e); The characteristic value of quartz lithology coefficient is generally 1.81 (b / e); The characteristic value of the calcite lithology coefficient is generally taken as 5.08 (b / e); The characteristic value of dolomite lithology coefficient is generally 3.14 (b / e).

9. The method for predicting the vertical sweet spot of high-siliceous shale according to claim 1, characterized in that: In step S5, the verification of the accuracy of the shale sweet spot includes: S501, comparing the relative content data of siliceous minerals measured in the laboratory in step S1 with the relative content data of siliceous minerals calculated by well logging in step S3 to see whether they are consistent, so as to determine whether the method for calculating the relative content of siliceous minerals is effective; S502, comparing the sweet spot calculated by logging in step S4 with the high value area of ​​TOC value and nuclear magnetic porosity obtained in step S2 to see whether they correspond, so as to determine whether the sweet spot is accurate.

10. The method for predicting the vertical sweet spot of high-siliceous shale according to claim 1, characterized in that: In step S1, the logging data is required to correspond one-to-one with the well depth and other data of the collected shale core samples, that is, the logging data at the same depth point and the measured experimental data correspond one-to-one.

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