阅读说明：本技术 基于主控要素地震-地质一体化分析构造煤分布预测方法 (Method for predicting distribution of tectonic coal based on master control element seismic-geological integrated analysis ) 是由 常锁亮 刘晶 张生 陈强 于 2021-08-24 设计创作，主要内容包括：本发明提供了一种基于主控要素地震-地质一体化分析构造煤分布预测方法,属于构造煤分布预测技术领域；具体通过选取残差、倾角、倾角突变和倾向突变作为构造煤构造控制要素的量化指标；选取煤层所在四级层序范围内砂泥厚度比和砂泥厚度比突变系数作为构造煤围岩控制要素的量化指标；选取煤厚和煤厚突变系数作为构造煤煤层控制要素的量化指标；采用灰色关联法对井点处碎粒煤和糜棱煤厚度之和占煤层总厚之比和地质要素量化指标进行关联分析,构建煤分布预测模型；本发明对构造煤发育细节刻画更丰富,分辨程度更高,避免了常规地震直接预测手段的多解性。(The invention provides a tectonic coal distribution prediction method based on master control element seismic-geological integrated analysis, belonging to the technical field of tectonic coal distribution prediction; specifically, residual errors, dip angles, dip angle mutation and tendency mutation are selected as quantitative indexes of the structural coal structural control elements; selecting a sand-mud thickness ratio and a sand-mud thickness ratio mutation coefficient in a four-level sequence range of the coal seam as quantization indexes of the control elements of the tectonic coal wall rock; selecting the coal thickness and the coal thickness mutation coefficient as the quantitative indexes of the control elements of the structural coal seam; performing correlation analysis on the ratio of the sum of the thicknesses of the crushed coal and the minced ridge coal at the well point to the total thickness of the coal bed and the geological element quantitative index by adopting a gray correlation method to construct a coal distribution prediction model; the invention has richer description on the development details of the tectonic coal and higher resolution degree, and avoids the multi-solution of the conventional earthquake direct prediction means.)

1. A method for predicting the distribution of structural coal based on the main control element seismic-geological integrated analysis is characterized by comprising the following steps:

a) selecting residual A₁Angle of inclination A₂Inclination angle mutation A₃And tendency mutation A₄The four parameters are used as quantitative indexes of the control elements of the structure coal;

b) selecting the sand-mud thickness ratio B in the range of the four-level sequence of the coal bed₁Thickness ratio mutation coefficient B of silt₂The quantitative indexes are used as control elements of the tectonic coal surrounding rock;

c) selecting coal thickness C for quantitatively representing control of thick coal zone and coal seam sudden thickening and thin belt on constructional coal₁And coefficient of coal thickness variation C₂The quantitative indexes are used as control elements of the tectonic coal seam;

d) adopting a grey correlation method to quantify the ratio H of the sum of the thicknesses of the crushed coal and the minced ridge coal at the well point to the total thickness of the coal bed and the geological factor A₁、A₂、A₃、A₄、B₁、B₂、C₁、C₂Performing correlation analysis, and calculating the correlation degree of each factor;

e) constructing a coal distribution prediction model:

calculating a comprehensive coefficient K: carrying out correlation analysis on the quantitative index values of the main control elements of the well points and the proportion of the tectonic coal to obtain a fitting function f (X)_n) The degree of association of the element is used as the control weight ρ of the element_nAnd finally, calculating a comprehensive coefficient K:

K＝K₁×ρ₁+K₂×ρ₂+...+K_n×ρ_n

K_n＝f(X_n)

where K is the overall coefficient, K_nThe ratio of the tectonic coal calculated by the single main control element and the fitting function; rho_nAre the weight coefficients of different master control elements; f (X)_n) The main control element quantitative parameters and the tectonic coal proportion fitting function; x_nIs the quantization parameter value (A) of the main control element₁、A₂、A₃、A₄、B₁、B₂、C₁、C₂)；g_kThe grey correlation degree between the main control element and the structural coal proportion;

and the second step of calculating the predicted tectonic coal ratio H: carrying out correlation analysis on the comprehensive coefficient K and the ratio of the tectonic coal at the well point to obtain a fitting function f (K), and then calculating the forecast ratio H of the tectonic coal according to the fitting function and the comprehensive coefficient:

H＝f(K)

wherein H is the tectonic coal prediction ratio, f (K) is a fitting function of the tectonic coal ratio and a comprehensive coefficient K;

f) and calculating the development degree of the whole-region tectonic coal by using a tectonic coal prediction model based on the main control elements and the seismic transverse high-density data of the main control elements.

2. The method of claim 1, wherein the residual A is a residual error of the prediction of the distribution of the coal based on the principal component seismic-geological integration analysis₁The calculation method comprises the following steps: fitting the elevation of the coal seam by using a least square method to obtain a trend value; then, subtracting the trend value from the original stratum elevation to obtain a residual error:

Z_i＝p₀+p₁f₁+p₂f₂+...+p_nf_n

in the formula: z_iIs the trend value (m), p_nIs the undetermined coefficient; f. of_nIs a fitting function; n is the maximum degree of fit;

A₁＝Z-Z_i

in the formula: a. the₁Is the residual (m), Z_iIs the trend value (m) and Z is the original formation elevation.

3. The method of claim 1 for constructing a coal distribution forecast based on key element seismic-geological integration analysisCharacterized by a coefficient of inclination abrupt change A₃The average value of the inclination angle change of a certain point in the rock stratum relative to the surrounding points is calculated by the inclination angle value:

in the formula: a. the₃Is the inclination angle mutation coefficient, D is the inclination angle;

the tendency mutation coefficient is an average value of the tendency change of a certain point in the rock stratum relative to the surrounding points, and is calculated by the tendency value:

in the formula: a. the₄Is the tendency mutation coefficient, I is the tendency.

4. The method for predicting the distribution of the main control element-based seismic-geological integrated analysis tectonic coal according to claim 1, characterized in that three-dimensional seismic data and drilling and logging data are used for carrying out construction fine interpretation to obtain a coal seam elevation and then calculating residual errors, and meanwhile, dip angle and dip tendency attributes are extracted, and dip angle mutation and dip tendency mutation coefficients are calculated.

5. The method for predicting the distribution of the structural coal based on the seismic-geological integration analysis of the main control elements as claimed in claim 1, wherein the sand-mud ratio in the four-level sequence of the coal bed is predicted by seismic sedimentation; and calculating the sand-mud ratio mutation coefficient after obtaining the sand-mud ratio.

6. The method for predicting the coal distribution based on the seismic-geological integration analysis of the main control elements as claimed in claim 1, wherein the coal thickness is predicted by seismic inversion method by using seismic and drilling logging data, and the coal thickness mutation coefficient is calculated after the coal thickness is obtained.

Technical Field

The invention belongs to the technical field of tectonic coal distribution prediction, and particularly relates to a tectonic coal distribution prediction method based on master control element earthquake-geology integration analysis.

Background

China coal-containing basins are mostly formed in the land phase or sea-land transition phase deposition environment, and the construction movement transformation of one or more stages is carried out in the later stage, so that the thickness and the structural space diversity of coal layers in the basins are strong, and the construction coal is generally developed. The development of the constructional coal in the coal bed not only seriously restricts the development of the coal bed gas, but also easily forms a coal and gas outburst dangerous area to influence the coal mining, so that the effective disclosure of the distribution condition of the constructional coal in the development scale coal bed has important significance for improving the development efficiency of the coal bed gas and realizing the safe and green mining of coal mines. At present, the distribution prediction research of domestic and overseas tectonic coals mainly focuses on regional geological inference and local geophysical identification, and the two methods have respective limitations on tectonic coal identification and are difficult to effectively guide production. The geological inference method has a macroscopic judgment on the tectonic coal, the geophysical method has a low distinguishable degree on physical property differences caused by the tectonic coal, and the developed tectonic coal distribution prediction is totally lack of a systematic and multi-technical-means fine characterization and comprehensive evaluation method.

Technical solution of prior art 1: different geological elements control the development degree and the space distribution form of the tectonic coal, so that the tectonic coal distribution can be predicted according to the geological rule under a certain condition, and a geological prediction method based on the geological distribution rule of the tectonic coal is formed. Because the coal seam is a weak layer in the coal-bearing stratum, the formation of the structural coal in the coal seam under the action of structural stress is generally considered, and the spread of the structural coal is directly controlled by the geological structure formed under the action of the structural stress and the sedimentary building related to the stress concentration of the stratum. Therefore, the regular distribution of the tectonic coal is the result of the combined action of the combination characteristics of the coal measure and the stratum and the movement history of the regional geologic structure, and the tectonic coal at different tectonic positions, the coal bed and the surrounding rock combination position is distributed in different regularity.

Fold structure, fracture structure and laminar slip structure all have comparatively obvious control action to the coal body deformation in the mining area, and fracture complexity, fold deformation degree and tectonic coal development degree are good positive correlation between the three, and the more intense fold deformation, the more complex fracture structure, laminar slip structure develop, the more serious coal body deformation, the more developed tectonic coal. The control of the coal seam on the constructional coal is mainly embodied in two aspects of thickness and structure, the thicker the coal seam is or the thickness is increased suddenly, the more developed the gangue inclusion in the coal seam, the more complicated the structural change, and the more developed the constructional coal. The coal-bearing stratum comprises hard rock formations such as limestone, sandstone and siltstone, and soft rock formations such as sandy mudstone, mudstone and coal bed, and usually, the relative comparative development of the structural coal is at the part of the hard rock such as sandstone and the like which develops around the coal bed in the coal-bearing stratum.

Disadvantages of prior art 1: the geological inference method judges the structural condition of a research area according to geological environment conditions to further infer the structural damage degree of the coal body, is limited by the research scale of the geological control theory of the structural coal and the macroscopicity of geological data, only can qualitatively evaluate the overall development condition of the regional structural coal, and the prediction result only can provide a certain degree of reference for the distribution condition of the regional structural coal in a large-scale range, so that the structural damage degree of the coal body and the distribution range of the structural coal in the development scale cannot be accurately depicted.

Technical solution of prior art 2: based on the difference between rock elasticity parameters such as longitudinal and transverse wave velocity, density, elastic modulus, shear modulus, lame coefficient, Poisson's ratio and the like and seismic response characteristics such as seismic wave frequency, phase, amplitude, AVO and the like of the constructional coal and the primary coal, the parameter characteristics are obtained by utilizing technologies such as seismic attribute, post-stack pre-stack inversion and the like so as to distinguish different structural coals, and the seismic prediction method of the constructional coal is gradually formed. The conventional prediction method mainly comprises a tectonic coal seismic attribute prediction technology based on attenuation attributes, curvature attributes, spectral decomposition attributes and the like, a tectonic coal post-stack inversion prediction technology based on post-stack characteristic parameter inversion, a tectonic coal pre-stack inversion prediction technology based on pre-stack elastic parameters and AVO inversion, a tectonic coal multi-wave inversion and joint inversion prediction technology.

Disadvantages of prior art 2: due to the fact that the coal-bearing stratum is strong in heterogeneity, the thickness and the structure of the coal seam and surrounding rocks of the coal seam are changed transversely, the coal seam reflected waves not only contain the response of coal body structure change, but also contain the response of coal thickness and surrounding rock change and the like, when the coal is predicted to be constructed through seismic data, whether seismic attribute technology or inversion technology is affected by various change factors, and prediction accuracy is low overall.

Technical solution of prior art 3: because the tectonic coal and the primary coal have obvious difference in the aspects of electrical property, density, radioactivity, hardness, porosity and the like, logging curves such as resistivity, density, natural gamma, sound wave and the like are generally used as input, and the tectonic coal is identified through man-machine interaction to form a logging prediction method of the tectonic coal. At present, many scholars make relevant researches and obtain certain achievements in the aspect of identifying coal body structures by using logging data such as resistivity logging, natural gamma logging, compensated density logging, acoustic time difference logging, compensated neutron logging and the like.

Disadvantages of prior art 3: the tectonic coal logging prediction technology is developed more mature at present, and can vertically identify tectonic coal with higher precision and thickness thereof, but the logging technology identification result is only a single thing and cannot be applied to the transverse accurate prediction of strong-heterogeneity coal seams, and the logging technology is far from meeting the coal body structure identification requirement for development when the drilling distribution of a research area is limited or the transverse change of a coal body structure is faster.

The existing tectonic coal geological prediction method is mainly used for qualitatively deducing the development condition of tectonic coal from the regional geological environment based on regional geological data, and is difficult to guide the identification of the tectonic coal under the size of a mining area; the prediction range of the logging method is limited, and the coal distribution of the whole area is difficult to be described in the face of ubiquitous complex geological conditions; the seismic method has limited prediction precision and strong multi-solution of prediction results. Therefore, no matter the indirect prediction method based on geology or the direct prediction method based on geophysical, effective prediction of the distribution of the structural coal in the development scale range is difficult to realize.

Disclosure of Invention

The invention overcomes the defects of the prior art and provides a method for predicting the distribution of the structural coal based on the main control element seismic-geological integrated analysis. Aiming at the practical demand of developing scale tectonic coal continuous distribution fine prediction, a tectonic coal distribution prediction idea based on geological control element earthquake-geological integrated recognition is provided, on one hand, from the tectonic coal geological control element, different types of geological control elements and quantitative characterization parameters of the tectonic coal are explored, and a geological theoretical basis is laid for the idea; on the other hand, starting from the control element earthquake fine identification, the earthquake multi-technology and multi-section fine extraction method of various elements is researched, and earthquake technical support is provided for the thought; meanwhile, a method for constructing a tectonic coal distribution prediction model based on geological control element seismic fine recognition is researched and constructed, an application-oriented terminal interface is provided for the thought, and a set of development-oriented tectonic coal fine recognition method based on geological and geophysical combination is formed.

In order to achieve the above object, the present invention is achieved by the following technical solutions.

S1: seismic-geological integrated identification of structural control elements

S1.1: the structural control elements can be divided into folds and faults: the folds are the wavy bends formed by rock strata under the action of stress, the coal seam serving as a soft interlayer in the stratum is easy to slide between layers in the bending process of the stratum, the shear stress generated by sliding acts on the folding turning ends of the coal seam and the wing parts are strongest, and the production practice shows that the common coal body structure at the part is seriously crushed; the fault is the obvious displacement of rock mass along two sides of a fracture surface under the action of tectonic stress, and the fracture surface generates strong friction and deformation in the displacement increasing process, so that the coal body near the fault deforms seriously. The stratum fluctuation at the fold bending part is obvious and can be indicated by stratum residual error obtained by trend surface analysis, the stratum inclination of two wings at the fold bending end is obviously changed, the coal seam inclination is larger when the fold wing part slides, the stratum inclination is larger and the inclination is changed rapidly due to dislocation at the fault development part, so the residual error (A) is selected₁) Inclination angle (A)₂) Sudden change of inclination angle (A)₃) And a tendency mutation (A)₄) The four parameters are used as quantitative indexes of the control elements of the structure coal.

A₁: the residual is a parameter for representing the development of stratum folds, and the larger the absolute value of the residual is, the larger the deformation degree of the folds is. The residual error calculation method comprises two steps: 1 fitting the elevation of the coal seam by using a least square method to obtain a trend value(see formula 1); 2 subtracting the trend value from the original formation elevation to obtain a residual error (see formula 2).

Z_i＝p₀+p₁f₁+p₂f₂+...+p_nf_n (1)

In the formula: z_iIs the trend value (m), p_nIs the undetermined coefficient; f. of_nIs a fitting function; n is the maximum fitness.

a₁＝Z-Z_i (2)

In the formula: a is₁Is the residual (m), Z_iIs the trend value (m) and Z is the original formation elevation.

A₂: dip is the angle of the formation from the horizontal (see fig. 1), with the greater the dip, the steeper the formation.

A₃: the dip break coefficient is an average value of changes in dip of a point in the formation with respect to surrounding points (see fig. 2), and can be calculated from the dip values (see formula 3).

In the formula: a is₃Is the inclination angle mutation coefficient, and D is the inclination angle.

A₄: the tendency is to the downward slope of the formation (see figure 1). The dip mutation coefficient is an average of dip changes of a point in the formation with respect to surrounding points (see fig. 2), and can be calculated from dip values (see formula 4).

In the formula: a is₄Is the tendency mutation coefficient, and I is the tendency, and the specific positions are shown in figure 1 and figure 2.

S1.2: in order to obtain the four parameters, three-dimensional seismic data and drilling and logging data are utilized to carry out construction fine interpretation, a residual error is calculated after the elevation of the coal seam is obtained, meanwhile, dip angle and tendency attributes are extracted, and dip angle mutation and tendency mutation coefficients are calculated, and the specific flow is shown in figure 3.

S2: seismic-geological integrated identification of surrounding rock control elements

S2.1: the surrounding rock control elements can be divided into sandstone thickness and sandstone-shale change within the four-level sequence range of the coal bed: the coal-bearing stratum generally comprises hard rocks such as sandstone and limestone, and soft rocks such as mudstone and coal bed, the coal bed as the soft rock is easy to cause stress concentration in the coal bed at the corresponding position in the deposition process due to the imbalance of the thickness of the hard rocks in the surrounding rock and the soft and hard rock properties, and the production practice shows that the coal at the position is constructed to develop. In order to quantitatively characterize the phenomenon of uneven properties of the coal-bearing rock series sand-mud, the sand-mud thickness ratio (B) in the range of the four-level sequence of the coal bed is selected₁) Thickness ratio coefficient of sand to mud (B)₂) The quantitative index is used as a quantitative index of the control element of the tectonic coal surrounding rock.

B₁The sand-mud ratio refers to the ratio of the thickness of sandstone to the thickness of mudstone in the range of the four-level sequence of the coal bed.

B₂The sand-mud ratio mutation coefficient is an average value of sand-mud ratio change of a certain point in a rock stratum relative to surrounding points, and can be obtained by calculating the sand-mud ratio, and the calculation method is the same as the shape mutation coefficient.

S2.2: in order to obtain the sand-mud ratio in the range of the four-level sequence of the coal bed, the sand-mud ratio in the four-level sequence of the coal bed is predicted by using seismic and drilling logging information through a seismic sedimentology related technology. And calculating the sand-mud ratio mutation coefficient after obtaining the sand-mud ratio, and referring to a specific flow chart in figure 4.

S3: earthquake-geology integrated identification of coal bed control elements

S3.1: the coal bed type control elements can be divided into two types of coal thickness and coal thickness mutation: the coal bed belongs to a weak rock stratum in the stratum, the strength of the position of the coal bed is weaker as the coal bed is thicker, the stress is easily concentrated at the position, and the tectonic coal is developed; the laminar slip causes the coal to creep, which causes the coal seam to produce a spatially abrupt thickening and thinning strip in the shape of a strip, a lens or a bead, and the structural damage of the coal in the area is serious. In order to quantitatively characterize the control of the thick coal zone and the coal layer suddenly thickened and thinned to the structural coal, the coal thickness (C) is selected₁) And coefficient of coal thickness variation (C)₂) The quantitative index is used as a quantitative index of the control elements of the structural coal seam.

C₁Coal thickness means the absolute thickness of the coal seam.

C₂The coal thickness mutation coefficient is the average value of the coal thickness variation of a certain point in the coal bed relative to the surrounding points, and can be obtained by calculating the coal thickness value, and the calculation method is the same as the shape mutation coefficient.

S3.2: in order to obtain the coal thickness parameter, the earthquake and the drilling logging data are used for predicting the coal thickness by an earthquake inversion method, the coal thickness mutation coefficient is calculated after the coal thickness is obtained, and the specific flow is shown in figure 5.

S4: tectonic coal distribution prediction model construction

The horizontal high-density distribution data of various control elements of the constructional coal are obtained through multiple means and technologies of earthquake, and for different coal beds in different research areas, the development conditions of various geological elements are different, and the control action degrees on the constructional coal are different. In order to predict the development degree of the tectonic coal by integrating various factors, the main control geological factors of the tectonic coal in the target coal bed are firstly screened by grey correlation analysis, and then a tectonic coal prediction model is established by the correlation analysis between the main control factors and the tectonic coal proportion.

S4.1: master control element screening based on grey correlation analysis

In order to screen main control elements of the development of structural coal of a target coal bed and eliminate geological elements with low control degree or no control effect, a grey correlation method is adopted to calculate the ratio (H) of the sum of the thicknesses of the crushed coal and the minced arris coal at a well point to the total thickness of the coal bed and a quantitative index (A) of the geological elements₁、A₂、A₃、A₄、B₁、B₂、C₁、C₂) And performing correlation analysis and calculating the correlation degree of each factor. The higher the degree of association is, the larger the influence of the parameter on the development of the tectonic coal is, and generally the influence of the element can be considered to be not negligible when the degree of association reaches 60%, so that the geological element with the degree of association more than 60% is used as the main control element for the development of the tectonic coal.

S4.2: construction coal distribution prediction model construction based on master control elements

In order to quantitatively predict the development degree of the tectonic coal in the whole area, a tectonic coal prediction model is established by the main control elements and the tectonic coal proportion of the correlation analysis, and the modeling is divided into 2 steps:

calculating a comprehensive coefficient K: carrying out correlation analysis on the quantitative index values of the main control elements of the well points and the proportion of the tectonic coal to obtain a fitting function f (X)_n) The degree of association of the element is used as the control weight ρ of the element_nAnd finally, calculating a comprehensive coefficient K:

K＝K₁×ρ₁+K₂×ρ₂+...+K_n×ρ_n (5)

K_n＝f(X_n) (6)

where K is the overall coefficient, K_nThe ratio of the tectonic coal calculated by the single main control element and the fitting function; rho_nAre the weight coefficients of different master control elements; f (X)_n) The main control element quantitative parameters and the tectonic coal proportion fitting function; x_nIs the quantization parameter value (A) of the main control element₁、A₂、A₃、A₄、B₁、B₂、C₁、C₂)；g_kIs the grey correlation degree between the main control element and the proportion of the tectonic coal.

And the second step of calculating the predicted tectonic coal ratio H: carrying out correlation analysis on the comprehensive coefficient K and the ratio of the tectonic coal at the well point to obtain a fitting function f (K), and then calculating the forecast ratio H of the tectonic coal according to the fitting function and the comprehensive coefficient:

H＝f(K) (8)

wherein H is the tectonic coal forecast proportion, f (K) is a fitting function of the tectonic coal proportion and the comprehensive coefficient K.

And finally, calculating the development degree of the whole-region tectonic coal by using a tectonic coal prediction model based on the main control elements and the seismic transverse high-density data of the main control elements.

Compared with the prior art, the invention has the following beneficial effects:

the invention provides a tectonic coal prediction method based on master control geological factor earthquake-geology integration analysis, which not only comprehensively considers geological elements for controlling the development of tectonic coal, but also fully utilizes the advantages of a three-dimensional earthquake technology in the aspects of construction fine explanation, coal seam thickness prediction, lithology prediction and the like, converts the direct identification of tectonic coal by earthquake into the indirect identification of tectonic coal by identifying the geological master control factors of tectonic coal, and provides new ideas and attempts for tectonic coal distribution prediction. The method starts from the quantification of geological factors for controlling the development of the tectonic coal, the forecast result has richer description on the development details of the tectonic coal and higher resolution, the multi-solution of the conventional earthquake direct forecasting means is avoided, and the method is favorable for the fine explanation of the development degree of the tectonic coal in the development scale of the mining area.

The application of the example shows that the tectonic coal distribution prediction method based on the master control element earthquake-geology integration analysis has good identification effect on the development degree of the tectonic coal at well points and among wells, and can find corresponding geological causes for a tectonic coal high development area, so that reasonable suggestions can be provided for coal bed gas development and coal mining in the area, and the method has good practical application value.

Drawings

FIG. 1 is a stratigraphic attitude diagram; in the figure, α is the tilt angle and CD is the inclination.

FIG. 2 is a schematic diagram of a three-dimensional model mutation coefficient of a formation; in the figure, X and Y represent coordinate axes, Z represents a tilt angle or inclination, and P represents a calculation point.

Fig. 3 is a flow chart of the construction element parameter extraction.

FIG. 4 is a flow chart of sand-to-mud ratio prediction.

FIG. 5 is a flow chart of coal thickness prediction.

FIG. 6 is a diagram illustrating the prediction of coal distribution in a block 15 of the south of the waterline basin in accordance with an exemplary embodiment.

Detailed Description

In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail with reference to the embodiments and the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. The technical solution of the present invention is described in detail below with reference to the embodiments and the drawings, but the scope of protection is not limited thereto.

Step 1: performing structural interpretation on three-dimensional seismic data of a seismic exploration work area, extracting elevation data and performing trend surface analysis to obtain residual errors (A)₁) Attribute, extracting dip angle (A) for seismic data₂) And the tendency attribute, calculating to obtain the dip angle mutation (A)₃) And a tendency mutation (A)₄) An attribute.

Step 2: method for predicting sand-mud thickness ratio (B) of coal layer after coal gathering by using seismic sedimentology method₁) Attribute, calculating the sand-mud thickness ratio mutation coefficient (B)₂) An attribute.

And step 3: predicting coal seam thickness, i.e. coal thickness (C), using wave impedance inversion₁) Calculating the coal thickness mutation coefficient (C)₂)。

And 4, step 4: and (3) calculating the correlation between the tectonic coal ratio and the element parameters at the well point by a grey correlation method, and screening the main control elements for the tectonic coal development of the target coal bed.

And 5: and (4) carrying out correlation analysis on the relationship between the quantitative parameters of the main control elements and the proportion of the tectonic coal, and constructing a comprehensive prediction model of the main control elements.

Step 6: and predicting the ratio of the all-region tectonic coal by using a prediction model.

By utilizing the existing method and the invention to predict the coal proportion of 15 coal structures in a certain block in the south of the Qin Water basin, it can be seen that: most areas of No. 15 coal seams develop 10-20% of tectonic coal, more than 30% of tectonic coal development areas are mainly distributed in the middle and south of a research area, fault development of the tectonic coal development areas is realized, and the coal seam has a large inclination angle or larger sandstone thickness. The prediction results are tested through two verification wells M11 and M12, wherein the actual measurement ratio of the well M11 tectonic coal is 14%, the prediction ratio is 13.95%, the actual measurement ratio of the well M12 tectonic coal is 24%, the prediction ratio is 24.27%, and the prediction errors are less than 2%, so that the feasibility of the prediction method is proved.

While the invention has been described in further detail with reference to specific preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.