Well-ground electromagnetic multi-parameter-based shale gas favorable area identification method and system

Abstract

This invention discloses a method and system for identifying favorable shale gas areas based on well-to-surface electromagnetic multi-parameter methods, comprising: conducting two- or three-dimensional surface electromagnetic surveys in the area to be explored and acquiring surface electromagnetic data, and performing inversion imaging; the surface electromagnetic data includes a first apparent resistivity and a first apparent polarizability; obtaining several core samples by drilling within and outside the area to be explored, and measuring the second resistivity and second polarizability using laboratory methods; combining the second resistivity and second polarizability, and applying a weighted average method to correct the first apparent resistivity and first apparent polarizability accordingly, to obtain a third apparent resistivity and a third apparent polarizability; using cluster analysis to identify and extract the third apparent resistivity and third apparent polarizability respectively, to obtain the anomalous locations and spatial distribution patterns of low apparent resistivity and high apparent polarizability; and delineating favorable shale gas areas.

Description

Technical Field

[0001] This invention relates to the field of shale gas exploration technology, and in particular to a method and system for identifying favorable shale gas areas based on well-to-geomagnetic multi-parameters. Background Technology

[0002] Currently, shale gas exploration technologies are developing rapidly. Seismic exploration, due to its high resolution, is the primary method. However, in southern China, shale gas exploration areas are mostly complex mountainous regions with intricate geological conditions, making seismic exploration difficult and extremely costly. Electromagnetic exploration methods, on the other hand, offer advantages such as greater exploration depth, higher efficiency, and lower cost. Furthermore, shale gas reservoirs possess electromagnetic characteristics such as low resistivity and high polarizability. Therefore, electromagnetic exploration methods are used for area reconnaissance in shale gas exploration and as a supplement to seismic exploration. Commonly used methods include wide-area electromagnetic methods, time-frequency electromagnetic methods, magnetotellurics, and complex resistivity methods. It should be noted that the favorable shale gas area in this technology refers to the favorable target area for shale gas exploration.

[0003] For example, in Chinese invention patent CN105607147A, entitled "A Method and System for Inverting Shale Gas Reservoir Resistivity," the method includes: obtaining the apparent resistivity of the target area using a wide-area electromagnetic method; acquiring seismic data of the target area; and performing constrained inversion on the apparent resistivity based on the seismic data to obtain the distribution variation law of shale gas reservoir resistivity in the target area. This technology avoids the multiple solutions caused by using only seismic or electromagnetic methods for inversion in existing technologies, and improves the accuracy and precision of shale gas reservoir resistivity inversion.

[0004] For example, the Chinese invention patent with publication number CN115097107A and titled "A Method for Identifying the Genetic Type of Low Resistivity Shale and Shale Gas Exploration Potential Based on New Resistivity Parameters" evaluates the gas content of a single well and the exploration potential of the corresponding structural unit from two perspectives: the genetic type of low resistivity shale and the gas content determined by field analysis. Specifically, it uses new resistivity parameters and deep lateral cross-plots to partition the low resistivity genesis of shale, and points the field analysis gas content data to the gas content range of the low resistivity genesis of shale. This can help production units quickly define the genetic type of low resistivity shale, quickly determine whether it has industrial production capacity, and evaluate the exploration potential of similar structural units, which is conducive to production units making quick decisions. This invention has extremely strong production guidance significance.

[0005] For example, the Chinese invention patent with publication number CN111188612A and titled "A Rapid Identification Method for Shale Oil Sweet Spots Based on Multi-Parameter Fusion of Well Logging" mainly includes the following steps: logging completed shale wells to obtain several logging curves; selecting compensated sonic curves, natural gamma curves, compensated density curves, and deep resistivity curves as sensitive logging curves; linearly transforming the compensated sonic curves, natural gamma curves, and compensated density curves using the deviation standardization method to obtain standardized compensated sonic curves, natural gamma curves, and compensated density curves; selecting the resistivity values ​​of stably distributed mudstone sections to obtain standardized deep resistivity curves; and obtaining the shale oil comprehensive evaluation index curve based on the standardized sensitive logging curves. This invention method fully integrates multiple logging response characteristics, effectively improving the accuracy of sweet spot evaluation using logging data.

[0006] The paper "Study on Complex Resistivity of Well-to-Site Differential Electromagnetic Method and Its Application in Reservoir Oil Saturation Evaluation" starts with three-dimensional forward modeling using the well-to-site differential electromagnetic method (BSDEM). Based on experimental analysis of rock complex resistivity, it further studies complex resistivity models and parameter inversion for different frequency bands, constructs an oil saturation model based on dispersion rate / polarizability, proposes a BSDEM-based reservoir complex resistivity constrained inversion method, and forms a BSDEM-based complex resistivity reservoir evaluation method. In addition, the paper "Study on Joint Inversion of CSEM and Seismic Based on Cross-Gradient" proposes a three-dimensional CSEM and seismic joint inversion method based on a cross-gradient coupling mechanism, and also utilizes mean clustering and regression analysis techniques for adaptive correction during inversion iteration.

[0007] However, the above technology has the following problems:

[0008] First, most of the aforementioned technologies identify shale gas-promoting areas from the perspective of a single method, single attribute, or single parameter, or they are combined with costly seismic exploration methods. Due to the ambiguity of single parameters and the limitations of exploration resolution in electromagnetic exploration methods, they cannot fully realize their methodological advantages in shale gas exploration.

[0009] Second, the accuracy of identifying favorable shale gas areas using a single attribute or parameter is low. It is limited by a single attribute or parameter. If the acquired parameters or data contain local anomalies or errors in the data collection, it directly leads to errors in the identification of favorable areas.

[0010] Therefore, there is an urgent need to propose a logically simple, accurate and reliable method and system for identifying shale gas favorable areas based on well-to-geomagnetic multi-parameters. Summary of the Invention

[0011] To address the aforementioned problems, the present invention aims to provide a method and system for identifying favorable shale gas areas based on well-to-geomagnetic multi-parameter analysis. The technical solution adopted by the present invention is as follows:

[0012] The first part of this invention provides a method for identifying favorable shale gas areas based on well-to-geomagnetic multi-parameter parameters, which includes the following steps:

[0013] Two- or three-dimensional ground electromagnetic detection is performed in the area to be detected, and ground electromagnetic data is acquired and inverted for imaging; the ground electromagnetic data includes a first apparent resistivity and a first apparent polarizability;

[0014] Several rock cores were obtained by drilling in and outside the area to be detected, and the second resistivity and second polarizability were measured by laboratory method.

[0015] By combining the second resistivity and the second polarizability, and using a weighted average method to correct the first apparent resistivity and the first apparent polarizability accordingly, the third apparent resistivity and the third apparent polarizability are obtained.

[0016] Cluster analysis was used to identify and extract the third apparent resistivity and the third apparent polarizability, respectively, to obtain the abnormal locations and spatial distribution patterns of low apparent resistivity and high apparent polarizability.

[0017] The overlapping areas of the anomalous locations and spatial distribution patterns of low apparent resistivity and high apparent polarizability are the favorable areas for shale gas.

[0018] The second part of this invention provides a shale gas favorable area identification system based on well-to-geomagnetic multi-parameters, which includes:

[0019] The ground electromagnetic data acquisition module performs two- or three-dimensional ground electromagnetic detection in the area to be detected and acquires ground electromagnetic data, which is then used for inversion imaging. The ground electromagnetic data includes a first apparent resistivity and a first apparent polarizability.

[0020] The input module is used to input the second resistivity and the second polarizability. The acquisition of the second resistivity and the second polarizability includes the following steps: drilling several rock cores distributed in and outside the area to be detected, and measuring the second resistivity and the second polarizability using laboratory methods.

[0021] The correction module is connected to the ground electromagnetic data acquisition module and the input module. It combines the second resistivity and the second polarizability and uses a weighted average method to correct the first apparent resistivity and the first apparent polarizability to obtain the third apparent resistivity and the third apparent polarizability.

[0022] The clustering analysis module, connected to the correction module, uses clustering analysis to identify and extract the third apparent resistivity and the third apparent polarizability, respectively, to obtain the abnormal locations and spatial distribution patterns of low apparent resistivity and high apparent polarizability.

[0023] Additionally, the annotation module, connected to the cluster analysis module, identifies overlapping areas of anomalous locations and spatial distribution patterns with low apparent resistivity and high apparent polarizability, which are the favorable areas for shale gas.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] (1) This invention starts from the electromagnetic characteristics of shale gas, and uses electromagnetic methods to detect and obtain the first apparent resistivity and the first apparent polarizability; then, it uses core samples for laboratory testing to obtain the second resistivity and the second polarizability. This invention uses a combination of multiple methods and parameters, which reduces the ambiguity of single methods and parameters. At the same time, each method is processed independently and mutually verified, which further improves the identification accuracy of electromagnetic methods in shale gas exploration.

[0026] (2) The present invention combines the second resistivity and the second polarizability, and uses a weighted average method to make corresponding corrections to the first apparent resistivity and the first apparent polarizability, so as to ensure that the data for cluster analysis is accurate and reliable, and further improve the accuracy of identification.

[0027] (3) This invention targets the low resistivity and high polarizability electromagnetic characteristics of shale gas, employing cluster analysis to obtain corresponding cluster centers, thereby identifying the anomalous locations and spatial distribution patterns of low apparent resistivity and high apparent polarizability. The intersection of these clusters yields accurate and reliable favorable shale gas zones, demonstrating both accuracy and reliability, and employing a simple logical approach.

[0028] In summary, this invention has the advantages of simple logic and high accuracy and reliability, and has high practical and promotional value in the field of shale gas exploration technology. Attached Figure Description

[0029] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope of protection. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a logic flowchart of the present invention.

[0031] Figure 2 This is a first apparent resistivity cross-sectional view of the present invention.

[0032] Figure 3 This is a cross-sectional view of the first apparent polarizability of the present invention.

[0033] Figure 4 This is a graph showing the second resistivity result obtained from indoor testing according to the present invention.

[0034] Figure 5 This is a graph showing the second polarizability result obtained from the indoor test of this invention.

[0035] Figure 6 This is a map showing the shale gas favorable area delineation according to the present invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this application clearer, the present invention will be further described below with reference to the accompanying drawings and embodiments. The embodiments of the present invention include, but are not limited to, the following embodiments. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0037] In this embodiment, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0038] The terms "first" and "second," etc., used in the specification and claims of this embodiment are used to distinguish different objects, not to describe a specific order of objects. For example, "first target object" and "second target object," etc., are used to distinguish different target objects, not to describe a specific order of target objects.

[0039] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0040] In the description of the embodiments in this application, unless otherwise stated, "multiple" means two or more. For example, multiple processing units means two or more processing units; multiple systems means two or more systems.

[0041] like Figures 1 to 6 As shown, this embodiment provides a method for identifying favorable shale gas areas based on well-to-geomagnetic multi-parameters, which includes the following steps:

[0042] The first step involves conducting two- or three-dimensional terrestrial electromagnetic (TEM) surveys in the area to be probed, acquiring TEM data, and performing inversion imaging. The TEM data includes the first apparent resistivity and the first apparent polarizability, such as... Figure 2 and Figure 3 As shown.

[0043] In this embodiment, there are many specific methods that can be selected for the ground electromagnetic method, such as the time-frequency electromagnetic method and the wide-area electromagnetic method. Here, the time-frequency electromagnetic method is preferred, as it can simultaneously perform time-frequency and frequency-domain acquisition, obtaining parameters of the first apparent resistivity and the first apparent polarizability, which can significantly save economic costs. In this embodiment, after completing the field data acquisition, the data is preprocessed, including time-frequency conversion, normalization, and noise reduction.

[0044] In this embodiment, the apparent resistivity of the entire region is calculated by processing the frequency domain data. The first apparent resistivity of the region to be detected is obtained from the frequency domain data, and is expressed as:

[0045]

[0046] Where I represents the emission current; E x (ω) represents the electric field strength; ρ represents the first apparent resistivity of the uniform half-space; r represents the distance between the measuring point and the origin; l represents half the length from point A to point B of the transmitter; (x,y) represents the coordinates of the measuring point relative to the center point of the transmitter; ζ represents the coordinates of the current element in the transmitter cable; φ represents the angle between the measuring point and the origin; k represents the wave number; e represents the base of the natural logarithm.

[0047] The expression for the wave number k is:

[0048]

[0049] μ0=4π10 -7

[0050] ω represents angular frequency; i represents the complex unit; u0 represents the permeability of free space;

[0051] The first apparent resistivity of the uniform half-space was obtained using a numerical iterative method. ρ .

[0052] In addition, the first apparent polarizability η is obtained from the time-domain data. s Its expression is:

[0053]

[0054] in, express The secondary potential difference measured at time T; ΔV(T) represents the total field potential difference at time T when the power is supplied; time T is the instant when the power is cut off.

[0055] In this embodiment, the first apparent resistivity and the first apparent polarizability obtained above are used to perform gridding and interpolation to perform two- or three-dimensional imaging of the entire exploration area.

[0056] The second step involves drilling several core samples both within and outside the detection area. The second resistivity and second polarizability are then measured using laboratory methods. Figures 4 to 5 As shown.

[0057] In this embodiment, the complex resistivity of the core sample was measured indoors using an impedance testing instrument. Based on the real and imaginary parts of the measured complex resistivity value, the resistivity value at each frequency point of the sample was calculated, and its expression is as follows:

[0058] ρ(ω')=Z(ω')*π*(r') 2 / L'

[0059] Where ω' represents frequency; r' represents radius of the core sample; L' represents height of the core sample; Z(ω') represents impedance;

[0060] The real and imaginary parts of the complex resistivity are used as the second resistivity of the core.

[0061] In this embodiment, the second polarizability of the core is obtained using the dual Cole-Cole model, which is expressed as:

[0062]

[0063] Where ρ'0 represents the second resistivity at zero frequency; m1 represents the second polarizability at time τ1; m2 represents the second polarizability at time τ2; c1 and c2 represent frequency correlation coefficients, which are constants with values ​​ranging from 0 to 1; and i represents the complex unit.

[0064] The third step involves combining the second resistivity and the second polarizability, and then using a weighted average method to correct the first apparent resistivity and the first apparent polarizability accordingly, to obtain the third apparent resistivity and the third apparent polarizability.

[0065] The drilling location from the second step is projected onto the two-dimensional / three-dimensional results from the first step. A weighted average is then calculated between the second resistivity and second polarizability values ​​obtained from the indoor tests in the second step and the first apparent resistivity and first apparent polarizability at the corresponding location and depth in the first step. Here, apparent resistivity is used as an example:

[0066] The value of the third apparent resistivity K is obtained by using the value of the second resistivity K2 and the value of the first apparent resistivity K1. Its expression is:

[0067]

[0068] Where a1 represents the weighting coefficient corresponding to the first apparent resistivity; a2 represents the weighting coefficient corresponding to the second resistivity.

[0069] In this embodiment, the weighted average result is used as the control point, and the first apparent resistivity and the first apparent polarizability in the first step are re-grid and interpolated to obtain a more accurate two / three-dimensional imaging result.

[0070] The fourth step involves using cluster analysis to identify and extract the third apparent resistivity and third apparent polarizability, respectively, to obtain the abnormal locations and spatial distribution patterns of low apparent resistivity and high apparent polarizability. In the cluster analysis for identifying and extracting the third apparent resistivity and third apparent polarizability, regions corresponding to 50% of the average apparent resistivity (which is less than the third apparent resistivity) are designated as regions corresponding to low apparent resistivity; regions corresponding to 150% of the average apparent polarizability (which is greater than the third apparent polarizability) are designated as regions corresponding to high apparent polarizability.

[0071] In this embodiment, K-means clustering is used to identify and extract low-resistivity and high-polarization anomalies from the two / three-dimensional apparent resistivity and apparent polarizability results in the third step. K-means clustering is an unsupervised real-time clustering algorithm, widely used in cluster analysis due to its simplicity and efficiency. The algorithm uses distance as a similarity evaluation index, thus optimizing the standard measure function for evaluating clustering performance.

[0072] Here, taking the third apparent resistivity as an example, it includes the following steps:

[0073] (1) Obtain the third apparent resistivity corresponding to several data points and form a dataset X;

[0074] (2) Sort the third apparent resistivity in dataset X from largest to smallest, select the last K data points, and use them as the initial cluster centers C;

[0075] (3) Classify the dataset X according to the minimum distance algorithm to obtain several clusters;

[0076] (4) For any cluster class, update the cluster center and perform classification until the following formula is satisfied:

[0077]

[0078] Where J(C,X) represents the standard function for the third apparent resistivity clustering; Represents the i1th cluster center With the j-th third apparent resistivity X j The Euclidean distance between them.

[0079] Fifth, based on the fourth step, areas that simultaneously meet the characteristics of low resistivity and high polarizability can be classified as favorable shale gas areas, while areas that meet one of these characteristics can be classified as potentially favorable areas.

[0080] First, based on the low resistivity and high polarizability anomalies identified in step four, the location coordinates and depth information of the low resistivity and high polarizability are indexed in the two-dimensional / three-dimensional results using numerical indexing.

[0081] Then, the locations and depths that simultaneously satisfy the characteristics of low resistivity and high polarizability are classified as favorable shale gas zones.

[0082] Then, locations and depths satisfying either low resistivity or high polarizability are designated as potentially favorable shale gas zones. For example... Figure 6 As shown.

[0083] The above embodiments are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any changes made based on the design principles of the present invention, or any non-creative modifications made thereon, shall fall within the scope of protection of the present invention.

Claims

1. A shale gas favorable area identification method based on well-ground electromagnetic multi-parameters, characterized in that, Includes the following steps: Two- or three-dimensional ground electromagnetic detection is performed in the area to be detected, and ground electromagnetic data is acquired and inverted for imaging; the ground electromagnetic data includes a first apparent resistivity and a first apparent polarizability; Several rock cores were obtained by drilling in and outside the area to be detected, and the second resistivity and second polarizability were measured by laboratory method. By combining the second resistivity and the second polarizability, and using a weighted average method to correct the first apparent resistivity and the first apparent polarizability accordingly, the third apparent resistivity and the third apparent polarizability are obtained. Cluster analysis was used to identify and extract the third apparent resistivity and the third apparent polarizability, respectively, to obtain the abnormal locations and spatial distribution patterns of low apparent resistivity and high apparent polarizability. The overlapping areas of the anomalous locations and spatial distribution patterns of low apparent resistivity and high apparent polarizability are the favorable areas for shale gas.

2. The method according to claim 1, wherein, In the process of identifying and extracting the third apparent resistivity and the third apparent polarizability using cluster analysis, the region corresponding to the average apparent resistivity that is less than the third apparent resistivity (50%) is designated as the region corresponding to low apparent resistivity; and the region corresponding to the average apparent polarizability that is greater than the third apparent polarizability (150%) is designated as the region corresponding to high apparent polarizability.

3. The method for identifying favorable shale gas areas based on well-to-geomagnetic multi-parameters according to claim 1, characterized in that, Two- or three-dimensional ground electromagnetic methods are used to detect the area to be detected and to acquire ground electromagnetic data; the two- or three-dimensional ground electromagnetic methods are time-frequency electromagnetic methods or wide-area electromagnetic methods.

4. The method for identifying favorable shale gas areas based on well-to-geomagnetic multi-parameters according to claim 3, characterized in that, The two / three-dimensional terrestrial electromagnetic method is a time-frequency electromagnetic method, which acquires frequency domain data and time domain data; it also includes: The first apparent resistivity of the region to be detected is obtained from the frequency domain data and is expressed as follows: ； Where I represents the emission current; Indicates electric field strength; The first apparent resistivity of a uniform half-space is represented by ; This represents the distance between the measuring point and the origin of the coordinate system. This represents half the length from point A to point B of the emission source; This indicates the coordinates of the measuring point relative to the center point of the transmitting source; Indicates the coordinates of the current element in the transmitting source cable; This represents the angle between the measuring point and the origin of the coordinate system. Indicates wave number; The base of the natural logarithm; The wave number The expression is: ； ； Indicates angular frequency; Indicates the complex unit; Indicates the permeability of free space; The first apparent resistivity of the uniform half-space was obtained using a numerical iterative method. .

5. The method for identifying favorable shale gas areas based on well-to-geomagnetic multi-parameters according to claim 4, characterized in that, Also includes: The first apparent polarization rate was obtained from the time-domain data. Its expression is: ； in, express The secondary potential difference measured at time t; It represents the total field potential difference at time T when the power is supplied; time T is the instant when the power is cut off.

6. The method for identifying favorable shale gas areas based on well-to-geomagnetic multi-parameters according to claim 1, characterized in that, The second resistivity is measured using a laboratory method, including the following steps: The complex resistivity of the rock core was measured using an impedance testing instrument. Its expression is: ； in, Indicates frequency; Indicates the radius of the core sample; Indicates the height of the rock core sample; Indicates impedance; The real and imaginary parts of the complex resistivity are used as the second resistivity of the core.

7. The method for identifying favorable shale gas areas based on well-to-geomagnetic multi-parameters according to claim 6, characterized in that, The second polarizability was measured using laboratory methods, including: The second polarizability of the core was obtained using the dual Cole-Cole model, and it is expressed as follows: ； in, The second resistivity is represented when the frequency is zero; express The second polarizability at time t; express The second polarizability at time t; and This represents the frequency correlation coefficient, which is a constant. It represents a complex unit.

8. The method for identifying favorable shale gas areas based on well-to-geomagnetic multi-parameters according to claim 1, characterized in that, By combining the second resistivity and the second polarizability, and using a weighted average method to correct the first apparent resistivity and the first apparent polarizability accordingly, the third apparent resistivity and the third apparent polarizability are obtained. The determination of the third apparent resistivity includes the following steps: Using the value of the second resistivity and the value of the first apparent resistivity Calculate the value of the third apparent resistivity Its expression is: ； in, This represents the weighting coefficient corresponding to the first apparent resistivity; This represents the weighting coefficient corresponding to the second resistivity.

9. The method for identifying favorable shale gas areas based on well-to-geomagnetic multi-parameters according to claim 1, characterized in that, Cluster analysis was used to identify and extract the third apparent resistivity and the third apparent polarizability. The identification and extraction of the third apparent resistivity included the following steps: Obtain the third apparent resistivity corresponding to several data points and form a dataset X; Sort the third apparent resistivity in dataset X from largest to smallest, select the last K data points, and use them as the initial cluster centers C; where K is a positive integer. The dataset X is classified using the minimum distance algorithm, resulting in several clusters. For any cluster class, update the cluster centers and perform classification until the following formula is satisfied: ； in, The standard function representing the third apparent resistivity clustering; Indicates the first Cluster centers With the Third apparent resistivity The Euclidean distance between them.

10. A shale gas favorable area identification system based on well-to-geomagnetic multi-parameters, characterized in that, include: The ground electromagnetic data acquisition module performs two- or three-dimensional ground electromagnetic detection in the area to be detected and acquires ground electromagnetic data, which is then used for inversion imaging. The ground electromagnetic data includes a first apparent resistivity and a first apparent polarizability. The input module is used to input the second resistivity and the second polarizability. The acquisition of the second resistivity and the second polarizability includes the following steps: drilling several rock cores distributed in and outside the area to be detected, and measuring the second resistivity and the second polarizability using laboratory methods. The correction module is connected to the ground electromagnetic data acquisition module and the input module. It combines the second resistivity and the second polarizability and uses a weighted average method to correct the first apparent resistivity and the first apparent polarizability to obtain the third apparent resistivity and the third apparent polarizability. The clustering analysis module, connected to the correction module, uses clustering analysis to identify and extract the third apparent resistivity and the third apparent polarizability, respectively, to obtain the abnormal locations and spatial distribution patterns of low apparent resistivity and high apparent polarizability. Additionally, the annotation module, connected to the cluster analysis module, identifies overlapping areas of anomalous locations and spatial distribution patterns with low apparent resistivity and high apparent polarizability, which are the favorable areas for shale gas.

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