System, method, equipment and medium for evaluating effectiveness of mudstone biological gas reservoir

Abstract

The invention relates to the technical field of unconventional oil and gas reservoir effectiveness well logging interpretation and evaluation, in particular to a mudstone biological gas reservoir effectiveness evaluation system, method, equipment and medium. And establishing a shale content calculation model of the high-shale stratum by utilizing the correlation between the sand content index and the shale content, and calculating the shale content. According to the method, the shale content calculation precision is greatly improved, and the problems of reservoir leakage and the like in the shale content calculation process in the prior art are effectively solved. And then, calculating the effective porosity by utilizing the shale content, calculating the permeability by utilizing the shale content and the effective porosity, and evaluating the effectiveness of the mudstone biogas reservoir by utilizing the effective porosity and the permeability. The shale content and the reservoir physical property parameters calculated by the method are well consistent with core analysis data, the stratum condition can be truly reflected, the evaluation result is more accurate, and a reliable basis is provided for subsequent oil and gas exploitation. The problem that in the prior art, the mud rock biological gas reservoir judgment accuracy is low is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of well logging interpretation and evaluation of the effectiveness of unconventional oil and gas reservoirs, and in particular to a system, method, equipment and medium for evaluating the effectiveness of a mudstone biogas reservoir. Background Art

[0002] The potential tapping layer of mudstone biogas has the characteristics of weak diagenesis, weak cementation, loose lithology, high mud content, and thin reservoir. The reservoir characteristics are quite different from those of the main gas layer. From the produced mudstone gas wells, the mud content of the mudstone biogas target layer is higher than that of the main gas reservoir as a whole, and it is mainly thin interlayers. The mud content calculated by the natural gamma curve of the main gas reservoir will be difficult to identify and divide the reservoir in the mudstone gas layer, resulting in gas layer leakage. From the core physical property analysis data, the total porosity of sandstone and mudstone analysis is similar, both about 35%. The total porosity and permeability calculated by the main model in the mudstone section cannot reflect the differences between the reservoir and the surrounding rock, and between the reservoirs. Especially in the high mud content formation of the mudstone biogas reservoir, the main model cannot be used to evaluate the effectiveness of the reservoir.

[0003] At present, the main methods for calculating mud content at home and abroad are:

[0004] The determination of the shale content Vsh is of great significance in the quantitative interpretation of shaly sandstone reservoirs. Over the years, many theories and methods for calculating the shale content Vsh have been proposed. At present, the methods for obtaining the shale content Vsh can be roughly divided into two categories. One is based on rock physics experiments, using each measuring point to calculate a shale content Vsh, and then finding the optimal value. The other is based on well logging curves. When the rock contains shale, various well logging curves are more or less affected by the shale, and the degree of influence is determined by the shale content Vsh. When evaluating the characteristics of the rock, only when the shale content Vsh is known, the influence caused by the shale can be known, so that the influence of the shale can be corrected.

[0005] Generally speaking, it is better to use natural gamma or gamma spectrum or natural potential to calculate the mud content, but natural gamma requires that the reservoir contains no radioactive minerals except mud. Natural potential requires that the resistivity of formation water remains unchanged and that the composition of mud in the reservoir is the same as that of the adjacent mudstone. Calculating mud content using other logging curve methods requires more stringent conditions. The resistivity method requires that the porosity and water saturation of the reservoir be small.

[0006] Due to the characteristics of weak diagenesis, high mud content and thin interlayers in the mudstone biogas target layer, the changes in the natural gamma and natural potential curves of well logging are small; the traditional models for calculating the mud content Vsh using natural gamma: Larionov (1969), Steiber (1970), and Clavier (1971) are: when there are high-gamma non-clay minerals such as potassium feldspar and mica, the mud content Vsh calculated using natural gamma is too high. Summary of the invention

[0007] Aiming at the problem of low accuracy in evaluating the effectiveness of mudstone biogas reservoirs in the prior art, the present invention provides a method for evaluating the effectiveness of mudstone biogas reservoirs.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] The present invention provides a method for evaluating the effectiveness of a mudstone biogas reservoir, comprising the following steps:

[0010] Obtain neutron curve and natural gamma curve of well logging;

[0011] The neutron curve is normalized to obtain a normalized neutron curve, and the natural gamma curve is normalized to obtain a normalized natural gamma curve;

[0012] The normalized neutron curve and the normalized natural gamma curve are combined to construct a sand index curve;

[0013] Use the sand index curve to calculate the mud content;

[0014] Use the mud content to calculate the effective porosity;

[0015] Calculate permeability using shale content and effective porosity;

[0016] The effectiveness of mudstone biogas reservoirs is evaluated using effective porosity and permeability.

[0017] Furthermore, the neutron curve is normalized to obtain the normalized neutron curve as follows:

[0018] Get the maximum value and the minimum value of the neutron curve;

[0019] The normalized neutron curve value is calculated using the maximum and minimum values ​​of the neutron curve as follows:

[0020] DCN=(CNmax-CN) / (CNmax-CNmin) (1)

[0021] Wherein, DCN is the normalized neutron curve value, CNmax is the maximum value of the neutron curve, CNmin is the minimum value of the neutron curve, and CN is the neutron curve value;

[0022] Using the normalized neutron curve values, a normalized neutron curve is constructed.

[0023] Furthermore, the natural gamma curve is normalized to obtain a normalized natural gamma curve as follows:

[0024] Get the maximum value and minimum value of the natural gamma curve;

[0025] The normalized natural gamma curve value is calculated using the maximum value and the minimum value of the natural gamma curve. The method is:

[0026] DGR=(GRmax-GR) / (GRmax-GRmin) (2)

[0027] Wherein, DGR is the normalized neutron curve value, GRmax is the maximum value of the natural gamma curve, GRmin is the minimum value of the natural gamma curve, and GR is the value of the natural gamma curve;

[0028] A normalized natural gamma curve is constructed using the normalized natural gamma curve value.

[0029] Furthermore, the normalized neutron curve and the normalized natural gamma ray curve are combined to construct a sand index curve as follows:

[0030] Obtain normalized neutron curve value and normalized natural gamma curve value;

[0031] The normalized neutron curve value and the normalized natural gamma curve value are used to construct a sand index curve model, and the sand index is calculated using the sand index curve model. The method is as follows:

[0032] FSD=DCN-DGR (3)

[0033] Among them, FSD is the sand content index, DCN is the normalized neutron curve value, and DGR is the normalized natural gamma curve value;

[0034] Using the sand content index, a sand content index curve is constructed.

[0035] Furthermore, using the sand content index curve, the method for calculating the mud content is:

[0036] Obtain shale content data from core analysis;

[0037] The core analysis mud content data was fitted with the sand content index curve to establish a mud content calculation model. The method is as follows:

[0038] Vsh=a×eb×FSD (4)

[0039] Among them, Vsh is the shale content, a and b are the exponential function coefficients, and FSD is the sand content index;

[0040] The mud content is calculated using the mud content calculation model.

[0041] Furthermore, the method for calculating effective porosity using the shale content is:

[0042] Obtain core analysis to determine the correlation between clay porosity and mud content;

[0043] According to the correlation between clay porosity and mud content obtained from core analysis, a clay porosity calculation model was established;

[0044] Calculate the clay porosity using the clay porosity calculation model;

[0045] Obtain the density curve and neutron curve of well logging;

[0046] The total porosity is calculated using the density curve and neutron curve of the well logging;

[0047] Using clay porosity and total porosity, effective porosity is calculated.

[0048] Furthermore, using the shale content and effective porosity, the permeability is calculated as follows:

[0049] Obtain the correlation between irreducible water saturation, shale content and effective porosity from core analysis;

[0050] Based on the correlation between irreducible water saturation, shale content and effective porosity in core analysis, a calculation model for irreducible water saturation was established;

[0051] The irreducible water saturation is calculated using the irreducible water saturation calculation model;

[0052] Obtain the correlation between core analysis permeability and effective porosity and irreducible water saturation;

[0053] Based on the correlation between permeability and effective porosity and irreducible water saturation obtained from core analysis, a permeability calculation model was established.

[0054] The permeability is calculated using the permeability calculation model.

[0055] A mudstone biogas reservoir evaluation system, comprising:

[0056] Data acquisition module: used to obtain neutron curves and natural gamma curves of well logging;

[0057] Normalization processing module: used for normalizing the neutron curve to obtain a normalized neutron curve, and normalizing the natural gamma curve to obtain a normalized natural gamma curve;

[0058] Sand index curve construction module: used to combine the normalized neutron curve and the normalized natural gamma curve to construct the sand index curve;

[0059] Mud content calculation module: used to calculate the mud content using the sand index curve;

[0060] Effective porosity calculation module: used to calculate effective porosity using mud content;

[0061] Permeability calculation module: used to calculate permeability using mud content and effective porosity;

[0062] Mudstone biogas reservoir effectiveness evaluation module: used to evaluate the effectiveness of mudstone biogas reservoirs using effective porosity and permeability.

[0063] A terminal device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0064] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] The present invention provides a method for evaluating the effectiveness of a mudstone biogas reservoir. By comparing and analyzing rock physics experimental analysis data with logging response characteristics, it is found that when the mud content increases, the bound water of the formation increases as a whole, and the neutron logging value increases accordingly. Therefore, the neutron curve can reflect the sand content of the formation to a certain extent. The method combines the neutron curve with the natural gamma curve to construct a sand index calculation model for dividing a mudstone section into favorable reservoirs to calculate the sand index. When the sand index is ≤0, it characterizes a high mud cap layer. When the sand index is >0, it characterizes a sandstone reservoir. The larger the sand index, the more sand and less mud the formation contains. Based on this, a favorable gas-bearing layer section can be divided in a high mud formation. By using the correlation between the sand index and the mud content, a mud content calculation model for a high mud formation is established to calculate the mud content. The method greatly improves the calculation accuracy of the mud content and effectively solves the problems of reservoir leakage in the process of calculating the mud content in the prior art. Then, the effective porosity is calculated using the mud content, the permeability is calculated using the mud content and effective porosity, and the effectiveness of the mudstone biogas reservoir is evaluated using the effective porosity and permeability. This method takes the sand content index as the core, establishes a reservoir physical property parameter model, and forms a fine model for calculating clay porosity, effective porosity, irreducible water saturation and permeability with the sand content index as the core, and provides a new method for evaluating the effectiveness of mudstone biogas reservoirs based on the sand content index. The mud content and reservoir physical property parameters calculated by the above method are consistent with the core analysis data, and can truly reflect the formation conditions. The sand content index model is used to identify mudstone biogas reservoirs, and the mud content, effective porosity, irreducible water saturation and permeability are used to evaluate the effectiveness of mudstone biogas reservoirs. The evaluation results are more accurate and reliable, providing a reliable basis for subsequent oil and gas production.

[0067] The present invention also provides a mudstone biogas reservoir evaluation system, which realizes normalization of neutron curve to obtain normalized neutron curve, normalization of natural gamma curve to obtain normalized natural gamma curve, and construction of sand index curve by combining the normalized neutron curve with the normalized natural gamma curve through the arrangement of a data acquisition module, a normalization processing module, a sand index curve construction module, a mud content calculation module, an effective porosity calculation module, a permeability calculation module and a mudstone biogas reservoir effectiveness evaluation module; the sand index curve is used as the core to calculate the mud content, effective porosity and permeability; and the effectiveness evaluation of the mudstone biogas reservoir is realized by using the effective porosity and permeability, with high evaluation efficiency, accuracy and reliability.

[0068] The present invention also provides a terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, to implement the above method steps.

[0069] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 It is a schematic diagram of a method for evaluating the reservoir effectiveness of a mudstone biogas reservoir according to the present invention.

[0071] Figure 2 The invention discloses a graph of core analysis mud content data and sand index curve fitting in mud content calculation in mud biogas reservoir effectiveness evaluation.

[0072] Figure 3 The present invention provides a clay porosity calculation diagram of clay porosity data obtained through nuclear magnetic resonance analysis and a curve fitting diagram of mud content in the effectiveness evaluation of a mudstone biogas reservoir.

[0073] Figure 4 The invention discloses a data fitting diagram of the irreducible water saturation value of core analysis and the ratio of effective porosity to mud content in permeability calculation in the effectiveness evaluation of a mudstone biogas reservoir of the present invention.

[0074] Figure 5 The diagram is a result of well logging interpretation of mudstone biogas obtained by using the mudstone biogas reservoir effectiveness evaluation system of the present invention. DETAILED DESCRIPTION

[0075] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0076] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0077] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0078] In the description of the embodiments of the present invention, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. indicate an orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the product of the invention is usually placed when in use, it is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0079] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", which does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0080] In the description of the embodiments of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0081] The present invention is further described in detail below in conjunction with specific embodiments, which are intended to explain the present invention rather than to limit it.

[0082] See also Figure 1 The present invention discloses a method for evaluating the effectiveness of a mudstone biogas reservoir, comprising the following steps:

[0083] S1: Get the neutron curve and natural gamma curve of well logging;

[0084] S2: normalize the neutron curve to obtain a normalized neutron curve, and normalize the natural gamma curve to obtain a normalized natural gamma curve, specifically:

[0085] The method of normalizing the neutron curve to obtain the normalized neutron curve is:

[0086] Get the maximum value and the minimum value of the neutron curve;

[0087] The normalized neutron curve value is calculated using the maximum and minimum values ​​of the neutron curve as follows:

[0088] DCN=(CNmax-CN) / (CNmax-CNmin) (1)

[0089] Using the normalized neutron curve value, constructing a normalized neutron curve;

[0090] The method of normalizing the natural gamma curve to obtain the normalized natural gamma curve is:

[0091] Get the maximum value and minimum value of the natural gamma curve;

[0092] The normalized natural gamma curve value is calculated using the maximum value and the minimum value of the natural gamma curve. The method is:

[0093] DGR=(GRmax-GR) / (GRmax-GRmin) (2)

[0094] Using the normalized natural gamma curve value, a normalized natural gamma curve is constructed;

[0095] Among them, DCN is the normalized neutron curve, CNmax is the maximum value of the neutron curve, CNmin is the minimum value of the neutron curve, and CN is the neutron curve; DGR is the normalized neutron curve, GRmax is the maximum value of the natural gamma curve, GRmin is the minimum value of the natural gamma curve, and GR is the natural gamma curve.

[0096] S3: Combine the normalized neutron curve and the normalized natural gamma curve to construct a sand index curve, specifically:

[0097] Obtain normalized neutron curve value and normalized natural gamma curve value;

[0098] The sand content index curve model is constructed using the normalized neutron curve value and the normalized natural gamma curve value, and the sand content index is obtained using the sand content index curve model. The method is as follows:

[0099] FSD=DCN-DGR (3)

[0100] Using the sand content index, construct a sand content index curve;

[0101] Among them, FSD is the sand content index, DCN is the normalized neutron curve value, and DGR is the normalized natural gamma curve value;

[0102] In actual production, through the comparison and analysis of rock physics experimental analysis data and logging response characteristics, it is found that when the mud content increases, the formation bound water increases as a whole, and the neutron logging value increases accordingly. Therefore, the neutron curve can reflect the sand content of the formation to a certain extent. By combining the neutron with the natural gamma curve, a sand index calculation model for the division of favorable reservoirs in mudstone sections is constructed. When the sand index is ≤0, it represents a high mud cap layer, and when the sand index is >0, it represents a sandstone reservoir. The larger the sand index, the more sand and less mud the formation contains. Based on this, it can be used as a favorable reservoir indicator in the mudstone biogas target well section.

[0103] S4: Use the sand index curve to calculate the mud content, specifically:

[0104] Obtain the shale content data of core analysis; the shale content data of core analysis can be obtained through X-ray diffraction whole rock experimental analysis;

[0105] The core analysis mud content data was fitted with the sand content index curve to establish a mud content calculation model. Figure 2 , the method is:

[0106] Vsh=a×e b×FSD (4)

[0107] Among them, Vsh is the shale content, a and b are the exponential function coefficients, and FSD is the sand content index;

[0108] The mud content is calculated using the mud content calculation model.

[0109] S5: Use the shale content to calculate the effective porosity, specifically:

[0110] Obtain clay porosity from core experiment NMR analysis;

[0111] Obtain core analysis to determine the correlation between clay porosity and mud content;

[0112] Since the clay porosity analyzed by NMR has a good correlation with the mud content, a clay porosity model is established based on the clay porosity data analyzed by NMR and the mud content curve. The clay porosity model is used to calculate the clay porosity. Figure 3 , the method is:

[0113] Φclay=c×Vsh (5)

[0114] Among them, Φclay is the clay porosity, c is a constant, and Vsh is the shale content;

[0115] Obtain total porosity from core analysis, density curves and neutron curves from well logging;

[0116] The total porosity from core analysis is used to perform binary linear data fitting with the density curve and neutron curve of well logging to establish a total porosity model and calculate the total porosity. The method is as follows:

[0117] Φt=a×CN+b×DEN+c (6)

[0118] Among them, Φt is the total porosity, CN is the neutron curve value, DEN is the density curve value, a is the neutron coefficient, b is the density coefficient, and c is a constant;

[0119] Using clay porosity and total porosity, the effective porosity is calculated as follows:

[0120] The total porosity Φt is corrected for shale, an effective porosity model is established, and the effective porosity is calculated as follows:

[0121] Φe=Φt-Φclay (7)

[0122] Among them, Φe is the effective porosity, Φt is the total porosity, and Φclay is the clay porosity.

[0123] S6: Calculate the permeability using the shale content and effective porosity as follows:

[0124] Obtain core analysis permeability and irreducible water saturation;

[0125] According to the core analysis permeability and irreducible water saturation, the correlation between the irreducible water saturation of core analysis and the shale content and effective porosity is obtained;

[0126] According to the correlation between irreducible water saturation and shale content and effective porosity in core analysis, a calculation model for irreducible water saturation is established. The method is to fit the irreducible water saturation value of core analysis with the ratio of effective porosity to shale content, establish the irreducible water saturation model, and calculate the irreducible water saturation. Figure 4 , specifically:

[0127]

[0128] Among them, Swi is irreducible water saturation, a and b are exponential function coefficients, Φe is effective porosity, and Vsh is shale content;

[0129] The core analysis permeability and the ratio of effective porosity to irreducible water saturation were linearly fitted to establish a permeability calculation model and calculate the permeability, specifically:

[0130]

[0131] Among them, K is the permeability, a is the coefficient, Φe is the effective porosity, and Swi is the irreducible water saturation.

[0132] S7: Use effective porosity and permeability to evaluate the effectiveness of mudstone biogas reservoirs. The lower limit of effective reservoir porosity is 23%, and the lower limit of permeability is 20mD.

[0133] A mudstone biogas reservoir evaluation system, comprising:

[0134] Data acquisition module: used to obtain neutron curves and natural gamma curves of well logging;

[0135] Normalization processing module: used for normalizing the neutron curve to obtain a normalized neutron curve, and normalizing the natural gamma curve to obtain a normalized natural gamma curve;

[0136] Sand index curve construction module: used to combine the normalized neutron curve and the normalized natural gamma curve to construct the sand index curve;

[0137] Mud content calculation module: used to calculate the mud content using the sand index curve;

[0138] Effective porosity calculation module: used to calculate effective porosity using mud content;

[0139] Permeability calculation module: used to calculate permeability using mud content and effective porosity;

[0140] Mudstone biogas reservoir effectiveness evaluation module: used to evaluate the effectiveness of mudstone biogas reservoirs using effective porosity and permeability.

[0141] Taking a well logging as an example, the effectiveness evaluation data and evaluation results obtained by using the above system are shown in Figure 5 And see the table below:

[0142]

[0143] Compared with the actual detection results, the results are consistent with the mudstone biogas reservoir data measured by actual core analysis and can truly reflect the formation conditions.

[0144] The present invention provides a terminal device including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor executes the computer program, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0145] The computer program may be divided into one or more modules / units, and the one or more modules / units are stored in the memory and executed by the processor to accomplish the present invention.

[0146] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0147] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0148] The memory may be used to store the computer programs and / or modules, and the processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory.

[0149] If the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0150] In summary, the present invention combines the neutron curve with the natural gamma curve to construct a sand index calculation model for dividing favorable reservoirs in mudstone sections to characterize sandstone reservoirs. The larger the sand index, the more sand and less mud the formation contains. Based on this, it can be used as a favorable reservoir indicator in the mudstone biogas target well section. With the sand index as the core, a reservoir physical property parameter model is established to analyze the correlation between effective porosity and permeability and clay bound water saturation, forming a fine model for calculating mud content, effective porosity, bound water saturation, and permeability with the sand index as the core. This method greatly improves the calculation accuracy of mud content and effectively solves problems such as reservoir leakage.

[0151] The above description is only a preferred embodiment of the present invention and is not intended to impose any limitation on the technical solution of the present invention. Those skilled in the art should understand that, without departing from the spirit and principles of the present invention, the technical solution can also be subjected to several simple modifications and substitutions, and these modifications and substitutions are also within the scope of protection covered by the claims.

Claims

1. A method for evaluating the effectiveness of a mudstone biogas reservoir, characterized in that: The following steps are involved: Obtain neutron curve and natural gamma curve of well logging; The neutron curve is normalized to obtain a normalized neutron curve, and the natural gamma curve is normalized to obtain a normalized natural gamma curve; The normalized neutron curve and the normalized natural gamma curve are combined to construct a sand index curve; Use the sand index curve to calculate the mud content; Use the mud content to calculate the effective porosity; Calculate permeability using shale content and effective porosity; The effectiveness of mudstone biogas reservoirs is evaluated using effective porosity and permeability.

2. The mudstone biogas reservoir evaluation method according to claim 1, characterized in that: The method of normalizing the neutron curve to obtain the normalized neutron curve is: Get the maximum value and the minimum value of the neutron curve; The normalized neutron curve value is calculated using the maximum and minimum values ​​of the neutron curve as follows: DCN=(CNmax-CN) / (CNmax-CNmin) (1) Wherein, DCN is the normalized neutron curve value, CNmax is the maximum value of the neutron curve, CNmin is the minimum value of the neutron curve, and CN is the neutron curve value; The normalized neutron curve is constructed using the normalized neutron curve values.

3. The mudstone biogas reservoir evaluation method according to claim 1, characterized in that: The method of normalizing the natural gamma curve to obtain the normalized natural gamma curve is: Get the maximum value and minimum value of the natural gamma curve; The normalized natural gamma curve value is calculated using the maximum value and the minimum value of the natural gamma curve. The method is: DGR=(GRmax-GR) / (GRmax-GRmin) (2) Wherein, DGR is the normalized neutron curve value, GRmax is the maximum value of the natural gamma curve, GRmin is the minimum value of the natural gamma curve, and GR is the value of the natural gamma curve; A normalized natural gamma curve is constructed using the normalized natural gamma curve value.

4. The mudstone biogas reservoir evaluation method according to claim 1, characterized in that: The method of combining the normalized neutron curve and the normalized natural gamma curve to construct the sand index curve is as follows: Obtain normalized neutron curve value and normalized natural gamma curve value; The normalized neutron curve value and the normalized natural gamma curve value are used to construct a sand index curve model, and the sand index is calculated using the sand index curve model. The method is as follows: FSD=DCN-DGR (3) Among them, FSD is the sand content index, DCN is the normalized neutron curve value, and DGR is the normalized natural gamma curve value; Using the sand content index, a sand content index curve is constructed.

5. The mudstone biogas reservoir evaluation method according to claim 1, characterized in that: Using the sand index curve, the method for calculating the mud content is: Obtain shale content data from core analysis; The core analysis mud content data was fitted with the sand content index curve to establish a mud content calculation model. The method is as follows: Vsh=a×e b×FSD (4) Among them, Vsh is the shale content, a and b are the exponential function coefficients, and FSD is the sand content index; The mud content is calculated using the mud content calculation model.

6. The mudstone biogas reservoir evaluation method according to claim 1, characterized in that: The method for calculating effective porosity using mud content is: Obtain core analysis to determine the correlation between clay porosity and mud content; According to the correlation between clay porosity and mud content obtained from core analysis, a clay porosity calculation model was established; Calculate the clay porosity using the clay porosity calculation model; Obtain the density curve and neutron curve of well logging; The total porosity is calculated using the density curve and neutron curve of the well logging; Using clay porosity and total porosity, effective porosity is calculated.

7. The mudstone biogas reservoir evaluation method according to claim 1, characterized in that: The method for calculating permeability using shale content and effective porosity is: Obtain the correlation between irreducible water saturation, shale content and effective porosity from core analysis; Based on the correlation between irreducible water saturation, shale content and effective porosity in core analysis, a calculation model for irreducible water saturation was established; The irreducible water saturation is calculated using the irreducible water saturation calculation model; Obtain the correlation between core analysis permeability and effective porosity and irreducible water saturation; Based on the correlation between permeability and effective porosity and irreducible water saturation obtained from core analysis, a permeability calculation model was established. The permeability is calculated using the permeability calculation model.

8. A mudstone biogas reservoir evaluation system, characterized in that: include: Data acquisition module: used to obtain neutron curves and natural gamma curves of well logging; Normalization processing module: used for normalizing the neutron curve to obtain a normalized neutron curve, and normalizing the natural gamma curve to obtain a normalized natural gamma curve; Sand index curve construction module: used to combine the normalized neutron curve and the normalized natural gamma curve to construct the sand index curve; Mud content calculation module: used to calculate the mud content using the sand index curve; Effective porosity calculation module: used to calculate effective porosity using mud content; Permeability calculation module: used to calculate permeability using mud content and effective porosity; Mudstone biogas reservoir effectiveness evaluation module: used to evaluate the effectiveness of mudstone biogas reservoirs using effective porosity and permeability.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

Images