A method and device for quantitatively evaluating deep coal rock gas reservoir space

Abstract

This invention discloses a method and apparatus for quantitatively evaluating the storage space of deep coal and rock gas reservoirs. The method includes: quantitatively evaluating the storage space of the target reservoir based on the measured volume percentages of pores with diameters within a first pore diameter range, a second volume percentage of pores with diameters within a second pore diameter range, a third volume percentage of pores with diameters within a third pore diameter range, a fourth volume percentage and a fifth volume percentage obtained after correcting the volume percentages of pores with diameters in the overlapping portions of the second and first pore diameter ranges and the overlapping portions of the third and second pore diameter ranges, as well as the measured average fracture aperture, porosity value, and development zone density. This method can accurately determine the distribution of pores and fractures in deep coal and rock reservoirs in complex superimposed basins with low pore and fracture structure damage, thereby accurately and quantitatively evaluating the storage space of coal and rock gas.

Description

Technical Field

[0001] This invention relates to the field of unconventional natural gas geological exploration technology, and in particular to a method and apparatus for quantitative evaluation of deep coal and rock gas reservoir space. Background Technology

[0002] The reservoir space of coalbed methane has a significant impact on the adsorption, porosity, and permeability of coal and the occurrence state of coalbed methane. It also affects the permeability and production characteristics of coal reservoirs to a certain extent. Shallow coalbed methane is mainly stored in the pores of the coal matrix in an adsorbed state. In deep coalbed methane reservoirs, the proportion of adsorbed gas decreases and the proportion of free gas increases. The reservoir space of adsorbed gas is mainly controlled by the porosity of the coal matrix, while the reservoir space of free gas is mainly controlled by the microfractures in the coal matrix. Microfractures include endogenous fractures (cleavages) and exogenous fractures. Moreover, complex superimposed basins have often undergone strong tectonic modification, making the reservoir space of deep coalbed methane in the basin more complex. Exogenous fractures and endogenous fractures become connected and overlap, the degree of fracture development increases, and the pore structure and its distribution vary greatly, which increases the difficulty of quantitatively evaluating the reservoir space of deep coalbed methane in complex superimposed basins.

[0003] Currently, carbon dioxide adsorption and low-temperature nitrogen adsorption methods are used to characterize the micropores of coal and rock. However, these gas adsorption methods require sample pulverization, causing some damage and disruption to the microporous structure. Furthermore, these methods cannot statistically analyze "closed pore" information. In addition, gas adsorption experiments must be conducted under low-temperature conditions, making it difficult to maintain consistent measurement conditions with other tests, thus affecting the accuracy of quantitative characterization of pore space. Visual characterization methods for the microfracture space of deep coal and rock free gas reservoirs mainly include stereomicroscopy and micron-scale CT scanning. Stereomicroscopy can characterize the width and distribution of microfractures, but it can only observe local information of the sample and cannot characterize the spatial distribution pattern. Therefore, there is an urgent need for a method that can quantitatively evaluate the deep coal and rock gas reservoir space in complex superimposed basins. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed to provide a method and apparatus for quantitative evaluation of deep coal and rock gas reservoir space that overcomes or at least partially solves the above problems.

[0005] In a first aspect, embodiments of the present invention provide a method for quantitatively evaluating deep coal and rock gas reservoir space, including:

[0006] The first volume percentage is obtained by measuring the volume percentage of pores in the target reservoir whose diameter falls within the first pore diameter range;

[0007] The volume percentage of pores whose inner diameter falls within the second pore diameter range of the target reservoir is measured to obtain the second volume percentage; the second pore diameter range partially overlaps with the first pore diameter range, and the maximum value of the second pore diameter range is greater than the maximum value of the first pore diameter range;

[0008] The volume percentage of pores whose inner diameter is located within the third pore diameter range of the target reservoir is measured to obtain the third volume percentage; the third pore diameter range partially overlaps with the second pore diameter range, the third pore diameter range does not overlap with the first pore diameter range, and the maximum value of the third pore diameter range is greater than the maximum value of the second pore diameter range;

[0009] Based on the first volume percentage and the second volume percentage, a fourth volume percentage is calculated, which represents the volume percentage of pores whose diameter is located in the overlapping part of the second pore diameter range and the first pore diameter range.

[0010] Based on the second volume percentage and the third volume percentage, a fifth volume percentage is calculated, which represents the volume percentage of pores whose diameters are located in the overlapping portion of the third pore diameter range and the second pore diameter range.

[0011] Measure the average opening of fractures with a length greater than a preset length within the target reservoir;

[0012] Calculate the cleavage porosity value of the target reservoir;

[0013] Calculate the development zone density of the target reservoir;

[0014] The reservoir space of the target reservoir is quantitatively evaluated based on the first volume percentage, the second volume percentage, the third volume percentage, the fourth volume percentage, the fifth volume percentage, the average opening, the cleavage porosity value, and the development zone density.

[0015] In one embodiment, calculating a fourth volume percentage based on the first volume percentage and the second volume percentage includes:

[0016] Based on the first volume percentage and the second volume percentage, as well as the preset first weighting coefficient and second weighting coefficient, the fourth volume percentage is calculated using the following formula:

[0017]

[0018] In the above formula, V1 represents the fourth volume percentage; f1 represents the first volume percentage; f1 represents the first weighting coefficient; V2 represents the second volume percentage; f2 represents the second weighting coefficient.

[0019] The first weighting coefficient represents the proportion of pores whose diameters are located in the overlapping portion of the second pore diameter range and the first pore diameter range, to pores whose diameters are located in the first pore diameter range.

[0020] The second weighting coefficient represents the proportion of pores whose diameter is located in the overlapping part of the second pore diameter range and the first pore diameter range, to the pores whose diameter is located in the second pore diameter range.

[0021] In one embodiment, calculating a fifth volume percentage based on the second volume percentage and the third volume percentage includes:

[0022] Based on the second volume percentage and the third volume percentage, as well as the preset third weighting coefficient and fourth weighting coefficient, the fifth volume percentage is calculated using the following formula:

[0023]

[0024] In the above formula, V1 represents the fourth volume percentage; V2 represents the second volume percentage; f3 represents the third weighting coefficient; V3 represents the third volume percentage; f4 represents the fourth weighting coefficient;

[0025] The third weighting coefficient represents the proportion of pores whose diameter is located in the overlapping part of the third pore diameter range and the second pore diameter range, to the pores whose diameter is located in the second pore diameter range.

[0026] The fourth weighting coefficient represents the proportion of pores whose diameter is located in the overlapping part of the third pore diameter range and the second pore diameter range, to the pores whose diameter is located in the third pore diameter range.

[0027] In one embodiment, measuring the volume percentage of pores in the target reservoir whose diameter falls within a first pore diameter range to obtain the first volume percentage includes:

[0028] Samples are prepared from the target reservoir according to a preset size, the samples are dried, and scattering images of all samples after drying are obtained.

[0029] Based on the scattering geometry, the curve of the relationship between scattering intensity and scattering angle corresponding to the scattering image is obtained. The first volume percentage is obtained by solving the curve of the relationship between scattering intensity and scattering angle.

[0030] In one embodiment, the target reservoir's reservoir space is quantitatively evaluated based on the first volume percentage, the second volume percentage, the third volume percentage, the fourth volume percentage, the fifth volume percentage, the average aperture, the cleavage porosity value, and the development zone density, including:

[0031] The pore structure of the target reservoir is quantitatively evaluated using the first volume percentage, the second volume percentage, the third volume percentage, the fourth volume percentage, and the fifth volume percentage.

[0032] The fracture structure of the target reservoir is quantitatively evaluated using the average aperture.

[0033] The porosity of the target reservoir is quantitatively evaluated using the cleavage porosity value.

[0034] The development zone structure of the target reservoir is quantitatively evaluated by development zone density.

[0035] In one embodiment, calculating the cleavage porosity value of the target reservoir includes:

[0036] Obtain the deep lateral resistivity curve and the shallow lateral resistivity curve;

[0037] Based on the deep lateral resistivity curve and the shallow lateral resistivity curve, the cleavage porosity value is calculated using the following formula:

[0038]

[0039] In the above formula, Φ f The porosity of the formation fracture is expressed in m. f R is the crack bonding index. m R is the resistivity of the drilling fluid filtrate. LLS and R LLD These are the shallow lateral resistivity and deep lateral resistivity of the formation, respectively.

[0040] In one embodiment, calculating the development zone density of the target reservoir includes:

[0041] The azimuth anisotropy characteristics of P-wave seismic attributes are obtained. Based on the azimuth anisotropy characteristics of the P-wave seismic attributes and the orientation angle data of the P-wave excitation direction relative to the fracture strike, the pre-constructed azimuth anisotropy equation is solved.

[0042] The azimuth anisotropy equation is as follows:

[0043] F(α) = A + Bcos 2α;

[0044] In the above formula, α represents the orientation angle of the P-wave excitation direction relative to the fracture strike; A represents the offset factor related to the offset distance; B represents the modulation factor related to the offset distance and fracture characteristics; F(α) is the azimuth anisotropy characteristic of the P-wave seismic properties.

[0045] The development zone density is calculated based on the values ​​of the offset factor related to the offset distance and the modulation factor related to the offset distance and the fracture characteristics.

[0046] In one embodiment, before solving the orientation anisotropy equation, the method further includes:

[0047] Data from N azimuth gathers are extracted from the profile of the target reservoir. The data from the N azimuth gathers are processed to obtain the corresponding azimuth offset data volumes.

[0048] From the N azimuth gathers, extract data from M azimuth / angle gathers according to a preset incident angle range, and obtain the corresponding azimuth / angle data volumes from the data of the M azimuth / angle gathers respectively;

[0049] Based on N azimuth offset data volumes and M azimuth / angle data volumes, seismic attribute parameter data related to fracture density are obtained; there are multiple seismic attribute parameters.

[0050] Seismic attribute fusion technology is used to normalize the seismic attribute parameter data to obtain the azimuth anisotropy characteristics of the fused seismic attributes.

[0051] Accordingly, the solution to the azimuth anisotropy equation is based on the azimuth anisotropy characteristics of the fused seismic attributes.

[0052] Secondly, embodiments of the present invention provide a quantitative evaluation device for deep coal and rock gas reservoirs, comprising:

[0053] The first measurement module is used to measure the volume percentage of pores in the target reservoir whose diameter is within the first pore diameter range;

[0054] The second measurement module is used to measure the percentage of pore volume in the target reservoir whose inner diameter is located within the second pore diameter range; the second pore diameter range partially overlaps with the first pore diameter range;

[0055] The third measurement module is used to measure the volume percentage of pores in the target reservoir whose diameter is located within the third pore diameter range, and to obtain the third volume percentage; the third pore diameter range partially overlaps with the second pore diameter range, and the third pore diameter range does not overlap with the first pore diameter range;

[0056] The first calculation module is used to calculate a fourth volume percentage based on the first volume percentage and the second volume percentage, wherein the fourth volume percentage represents the volume percentage of pores whose diameter is located in the overlapping part of the second pore diameter range and the first pore diameter range.

[0057] The second calculation module is used to calculate a fifth volume percentage based on the second volume percentage and the third volume percentage, wherein the fifth volume percentage represents the volume percentage of pores whose diameter is located in the overlapping part of the third pore diameter range and the second pore diameter range.

[0058] The fourth measurement module is used to measure the average opening of fractures with a length greater than a preset length within the target reservoir;

[0059] The third calculation module is used to calculate the cleavage porosity value of the target reservoir.

[0060] The fourth calculation module is used to calculate the development zone density of the target reservoir;

[0061] The quantitative evaluation module is used to quantitatively evaluate the reservoir space of the target reservoir based on the percentage of the number and volume of pores with diameters in the first pore diameter range, the percentage of the number and volume of pores with diameters in the second pore diameter range, the percentage of the number and volume of pores with diameters in the third pore diameter range, the average aperture, the cleavage porosity value, and the development zone density.

[0062] Thirdly, embodiments of the present invention provide a computer storage medium storing computer-executable instructions, which, when executed by a processor, implement the quantitative evaluation method for coal and rock gas storage space as described above.

[0063] Fourthly, embodiments of the present invention provide a terminal device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the quantitative evaluation method for coal and rock gas storage space as described above.

[0064] The beneficial effects of the above-described technical solutions provided in the embodiments of the present invention include at least the following:

[0065] The quantitative evaluation method for deep coal and gas reservoir space provided in this invention measure the volume percentage of pores in different pore diameter ranges. Specifically, the second pore diameter range partially overlaps with the first pore diameter range, and the third pore diameter range partially overlaps with the second pore diameter range, while the first and third pore diameter ranges do not overlap. For these two overlapping ranges, the volume percentage of pores is recalculated, resulting in the first, second, third, fourth, and fifth volume percentages for different pore diameter ranges without overlap. This achieves a microscopic quantitative evaluation of the reservoir space of the target reservoir. Furthermore, by measuring the average opening of fractures longer than a preset length, a quantitative evaluation of fractures is achieved, characterizing their spatial distribution and enabling precise three-dimensional visualization and quantitative characterization. Additionally, by calculating the cleavage porosity and development zone density, quantitative evaluation of fracture porosity and fracture development zones is achieved. This invention combines quantitative characterization of pore structure with quantitative characterization of fractures, ultimately achieving a quantitative characterization of deep coal and gas reservoir space in complex superimposed basins.

[0066] This invention utilizes scattering geometry to obtain the curve of the relationship between the scattering intensity and the scattering angle of the sample. By solving the curve of scattering intensity and scattering angle, the first volume percentage is obtained. This eliminates the need to crush the sample, avoiding damage to the microporous structure. It can also record the scattering information of micro-"open pores" in coal. Compared with the existing technology that uses the fluid intrusion method, this invention can also measure "closed pore" information, more accurately and quantitatively characterizing the pore storage space of coal.

[0067] To address the problem of quantitative planar evaluation of fractured reservoir space in deep coal and rock reservoirs in complex superimposed basins, this invention is based on a dual-lateral resistivity logging evaluation method. It calculates porosity to achieve the evaluation objective. Furthermore, it utilizes the variation of seismic P-wave amplitude and velocity with azimuth angle to detect fracture location and density, statistically analyzes the geometry, frequency, energy variation rate, and various seismic attributes of the seismic waves, and quantitatively calculates the density of fracture development zones to characterize the coal and rock gas reservoir space. This enables a macroscopic quantitative evaluation of the target reservoir's reservoir space.

[0068] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0069] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0070] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0071] Figure 1 This is a flowchart of a quantitative evaluation method for deep coal and rock gas reservoir space in Embodiment 1 of the present invention;

[0072] Figure 2 This is a schematic diagram of the process storage space of the method in Embodiment 1 of the present invention;

[0073] Figure 3 This is a flowchart of the method for achieving the first volume percentage in Embodiment 1 of the present invention;

[0074] Figure 4 This is a schematic diagram illustrating the principle of the small-angle scattering test method in Embodiment 1 of the present invention;

[0075] Figure 5 This is a flowchart of the method for calculating the porosity value of cleavage in Embodiment 1 of the present invention;

[0076] Figure 6 This is a flowchart of the fusion method in Embodiment 2 of the present invention;

[0077] Figure 7 This is an example diagram of the quantitative evaluation method for storage space in Embodiment 2 of the present invention;

[0078] Figure 8 This is a schematic diagram of the structure of a quantitative evaluation device for deep coal and rock gas storage space in an embodiment of the present invention. Detailed Implementation

[0079] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0080] To address the problem of the inability to quantitatively evaluate deep coal and rock gas reservoir space in existing technologies, embodiments of the present invention provide a method and apparatus for quantitatively evaluating deep coal and rock gas reservoir space.

[0081] Example 1

[0082] This invention provides a method for quantitatively evaluating deep coal and rock gas reservoir space, the process of which is as follows: Figure 1 As shown, it includes the following steps:

[0083] Step S101: Measure the volume percentage of pores in the target reservoir whose diameter is within the first pore diameter range to obtain the first volume percentage;

[0084] Step S102: Measure the volume percentage of pores in the target reservoir whose inner diameter is located within the second pore diameter range to obtain the second volume percentage; the second pore diameter range partially overlaps with the first pore diameter range, and the maximum value of the second pore diameter range is greater than the maximum value of the first pore diameter range;

[0085] Step S103: Measure the volume percentage of pores in the target reservoir whose inner diameter is located in the third pore diameter interval to obtain the third volume percentage; the third pore diameter interval partially overlaps with the second pore diameter interval, the third pore diameter interval does not overlap with the first pore diameter interval, and the maximum value of the third pore diameter interval is greater than the maximum value of the second pore diameter interval.

[0086] Step S104: Based on the first volume percentage and the second volume percentage, calculate the fourth volume percentage, which represents the volume percentage of pores whose diameters are located in the overlapping part of the second pore diameter range and the first pore diameter range.

[0087] Step S105: Based on the second volume percentage and the third volume percentage, calculate the fifth volume percentage, which represents the volume percentage of pores whose diameters are located in the overlapping part of the third pore diameter range and the second pore diameter range.

[0088] Step S106: Measure the average opening of fractures with a length greater than a preset length within the target reservoir;

[0089] Step S107: Calculate the cleavage porosity value of the target reservoir;

[0090] Step S108: Calculate the development zone density of the target reservoir;

[0091] Step S109: Quantitatively evaluate the reservoir space of the target reservoir based on the first volume percentage, second volume percentage, third volume percentage, fourth volume percentage, fifth volume percentage, average opening, cleavage porosity value and development zone density.

[0092] Schematic diagram of storage space (reference) Figure 2 As shown, Figure 2 This diagram illustrates the pore and fracture structure in deep coal-rock gas reservoirs, showing the intermingling of fractures and pores, with the proportion of free gas in microfractures being higher than that in pores.

[0093] In some optional embodiments, step S101 above is referred to Figure 3 As shown, this can be achieved through the following steps:

[0094] Step S201: Take samples from the target reservoir according to the preset size, dry the samples, and obtain the scattering images of all samples after drying.

[0095] Specifically, several samples of the same size are prepared from the target reservoir. For example, to facilitate small-angle X-ray scattering (SAXS) testing, samples with a cross-section of 1 cm are prepared. 2 Several sheet-like samples with a thickness of 1 mm were placed in a sample container and heated in a vacuum environment at 150℃ for 4 hours to remove moisture from the samples and prevent moisture from affecting light scattering, thereby improving the accuracy of the test. After heating, the samples were cooled to room temperature, and the coal scattering image of each sample was measured using a two-dimensional imaging plate detector. The coal scattering image characterizes the change in the intensity of scattered light from the sample with the scattering angle.

[0096] Step S202: Based on the scattering geometry, obtain the curve of scattering intensity versus scattering angle corresponding to the scattering image, solve the curve of scattering intensity versus scattering angle, and obtain the first volume percentage.

[0097] After obtaining the coal sample scattering image, the SR-SAXS software is used to perform data analysis on all the coal sample scattering images to obtain the initial scattering curve. Then, based on the scattering geometry, the initial scattering curve is converted into the corresponding relationship curve I(q) between the scattering intensity and the scattering angle (also called the scattering vector) q, as shown in the following formula (1):

[0098]

[0099] In equation (1) above, I is the scattering intensity (also called relative intensity); q is the scattering vector; I e For a single electron, N is the relative intensity; for each level, N is the number of particles; for each level, v is the electron density; for each level, V is the particle volume; and for each level, R is the particle volume. G The radius of gyration of the particle is the root mean square of the distances between all electrons of the particle and its center of mass.

[0100] By using the stepwise tangent method to solve formula (1), we obtain the following formula (2):

[0101]

[0102] In equation (2) above, n is the number of electrons in a particle, i represents the i-th size level, and R i N represents the gyroscopic radius of the particle at the i-th level. i Let be the number of particles at the i-th size level. Other parameters in the formula have been explained above and will not be repeated here in the embodiments of the present invention.

[0103] Based on the explanations of formulas (1) and (2) above, it can be understood that [R1…Ri Take the average value to obtain R G ;

[0104] Based on formula (2), define K i The volume distribution characterizing the scattering intensity of the i-th level particles; when q = 0 in the scattering intensity, we can obtain from formula (2):

[0105] I(0) = K1 + K2 + ... + K i (3)

[0106] Define W i Let W1 be the volume percentage for the i-th size level, then: W1: W2: ...: ...: (4)

[0107] Right now Therefore, the Iq curve is decomposed stepwise by the Jellinek tangent method, and a series of radii of gyration R are calculated from the series of slopes obtained. G Then, the radius of gyration R is obtained. G The volume percentage W of particles i (R G The specific calculation steps are as follows:

[0108] Pick: Taking the logarithm of both sides of the equation, we get:

[0109]

[0110] Then plot ln(I) as the ordinate and q2 as the abscissa, and use the slope to determine the slope. R can be obtained G The value of I can be obtained from the intercept K. e Nn 2 The value of R G Substituting R into formula (5) i , will I e Nn 2 Substituting K into formula (5) i Find W i The value of is the first volume percentage.

[0111] By observing a large number of samples using small-angle X-ray scattering (SAXS), the pore structure of coal and rock with diameters within the first pore diameter range (0 nm - 100 nm) can be observed. In other words, SAXS can characterize the micropore structure in the target reservoir. Compared with existing techniques that characterize micropores through gas adsorption methods (such as carbon dioxide adsorption and low-temperature nitrogen adsorption), SAXS does not require sample pulverization, thus avoiding damage to the micropore structure. SAXS can also record micro-open-pore scattering information. In addition, it can measure "closed-pore" information that cannot be measured using fluid intrusion methods, enabling a more accurate quantitative characterization of the pore storage space of coal and rock.

[0112] The principle of small-angle scattering test is as follows: Figure 4 As shown.

[0113] In some optional embodiments, the second pore diameter range is [50nm, 2000nm], and the pores in this range are called macropores. In step S102 above, the distribution of macropores is determined by high pressure mercury intrusion testing. Specifically, the sample is loaded into a sample tube, and vacuum sealing grease is evenly applied to the sandblasted opening of the sample tube. The inside of the sample tube is evacuated to a vacuum state and heated at 105°C for more than 12 hours. It should be noted that since the sample observed by small angle scattering method in step S101 does not damage the pore structure of the sample, in step S102, the sample in step S101 can be used directly, or several samples can be re-prepared from the target reservoir.

[0114] Using a high-pressure mercury intrusion porosimetry device, an initial pressure is applied to the inside of the heated sample tube to allow mercury to enter the pores of the sample. The initial and final pressures are determined based on the minimum pressure at which the sample can adsorb mercury and the minimum pressure at which it cannot adsorb mercury. During the pressurization process, the Lucas-Washburn equation is used to represent the relationship between pore diameter and pressure. The Washburn equation is shown below:

[0115] P = (-4γcosθ) / d; (7)

[0116] In the above formula (7), P is the pressure acting on the liquid surface, γ is the surface tension of mercury, which is taken as 0.48 N / m, θ is the contact angle of the wetting liquid, which is taken as 140°, and d is the pore diameter.

[0117] Based on the relationship between pressure and pore diameter, the pore distribution with diameter in the second pore diameter range can be obtained. Then, through the pore distribution with diameter in the second pore diameter range, the volume percentage of each level of pores in the range of [50nm, 2000nm] can be obtained, which is the second volume percentage.

[0118] As can be seen from the aforementioned ranges of the first and second pore diameter intervals, there is an overlap between them, and the overlap interval is [50nm-100nm]. In other words, both the small-angle scattering (SAS) and high-pressure mercury intrusion porosimetry methods measured the pore distribution within the [50nm-100nm] diameter range. To make the pore volume percentage results more accurate, the inventors of this invention used a weighted average of the two volume percentage results obtained from the overlap interval to obtain the pore volume percentage of the overlap interval, i.e., the fourth volume percentage. Specifically, the method for calculating the fourth volume percentage is as follows:

[0119] Based on the first volume percentage and the second volume percentage, and the preset first weighting coefficient and second weighting coefficient, the fourth volume percentage is calculated using the following formula:

[0120]

[0121] In equation (8) above, V1 represents the fourth volume percentage; f1 represents the first volume percentage; f1 represents the first weighting coefficient; V2 represents the second volume percentage; f2 represents the second weighting coefficient.

[0122] The first weighting coefficient represents the proportion of pores whose diameters are located in the overlapping portion of the second pore diameter range and the first pore diameter range, out of the total pores whose diameters are located in the first pore diameter range; the second weighting coefficient represents the proportion of pores whose diameters are located in the overlapping portion of the second pore diameter range and the first pore diameter range, out of the total pores whose diameters are located in the second pore diameter range.

[0123] In other words, the result of f1+f2 is not necessarily 1. Within the overlapping range of [50nm-100nm], the weighting coefficient of the first volume percentage measured by the small angle scattering test method decreases from 100% to 0% for the pore volume data within this overlapping range, while the weighting coefficient of the second volume percentage measured by the high pressure mercury intrusion test method increases from 0% to 100% for the pore volume data within this overlapping range.

[0124] In some optional embodiments, the diameter range of the third pore is [1μm~200μm]. Pores in this range can also be called microcracks. In step S103 above, the distribution of microcracks is determined using micron-scale CT scanning technology. Specifically, several samples are re-prepared from the target reservoir. The prepared samples are fixed in the center of the CT machine's turntable, and the height of the samples is adjusted to fix them in the center of the scanning area. For each sample, the turntable is rotated 0.9° during scanning, and one scan is performed to obtain a two-dimensional CT slice. The turntable is rotated multiple times to obtain multiple two-dimensional CT slices for each sample. The median filtering algorithm is used to denoise each obtained two-dimensional CT slice. The denoised two-dimensional CT slices are then input into visualization processing software (AVIZO software can be selected). The denoising process makes the two-dimensional CT slices clearer. In addition, To facilitate the analysis of 2D CT slices using AVIZO software, the denoised 2D CT slices can be optionally cropped, and then input into the AVIZO software. AVIZO employs the AVIZO watershed algorithm, analyzing multiple 2D CT slices of each sample to perform 3D reconstruction for each sample. In other words, the 3D reconstruction process is as follows: For each sample, the microcrack structure of the sample is constructed from multiple 2D CT slices taken from different angles; AVIZO analyzes multiple 2D CT slice images of the sample to obtain the porosity of each sample, which is in the form of a binary image. For each sample, based on multiple binary images, a stereo rendering is performed to obtain the geometric model of the pore space corresponding to the sample.

[0125] The sample is scanned using micron-scale CT scanning technology. Each sample needs to be rotated multiple times, and a scan is performed once for each rotation to obtain a two-dimensional CT slice. Although the more times the CT slice is scanned, the more accurate the two-dimensional CT slice is, the sample cannot be scanned indefinitely. Therefore, the embodiments of the present invention set a threshold to limit the number of scans for each sample.

[0126] To make the threshold setting more accurate, the porosity calculated by AVIZO software under different thresholds can be compared and analyzed with the porosity measured by micron CT scanning technology. Based on the analysis results, a reasonable threshold can be determined.

[0127] As can be seen from the aforementioned ranges of the second and third pore diameter intervals, there is an overlap between them, and the overlap interval is [1000nm-2000nm]. In other words, both the high-pressure mercury intrusion method and the micron-scale CT scanning method have measured the pore distribution with diameters in the [1000nm-2000nm] range. To make the pore volume percentage results more accurate, the inventors of this invention have used a weighted processing method on the two volume percentage results obtained from the overlap portion to obtain the pore volume percentage of the overlap portion, i.e., the fifth volume percentage. Specifically, the method for calculating the fifth volume percentage is as follows:

[0128] Based on the second and third volume percentages, and the preset third and fourth weighting coefficients, the fifth volume percentage is calculated using the following formula:

[0129]

[0130] In the above formula (9), V1 represents the fourth volume percentage; V2 represents the second volume percentage; f3 represents the third weighting coefficient; V3 represents the third volume percentage; f4 represents the fourth weighting coefficient;

[0131] The third weighting coefficient represents the proportion of pores whose diameters are located in the overlapping portion of the third pore diameter range and the second pore diameter range, out of the pores whose diameters are located in the second pore diameter range; the fourth weighting coefficient represents the proportion of pores whose diameters are located in the overlapping portion of the third pore diameter range and the second pore diameter range, out of the pores whose diameters are located in the third pore diameter range.

[0132] In some optional embodiments, step S106 above can be implemented in the following manner:

[0133] Several samples with dimensions of 50mm × 50mm were prepared from the target reservoir along the bedding direction. A stereomicroscope was used to photograph the fractures in three mutually perpendicular sections of each sample at a magnification of 10x. Each image was then processed and fracture extracted using ImageJ software, resulting in clearer images of the three mutually perpendicular sections of each sample. Cropping of the image edges was also possible. The images were then imported into Image-Pro Plus software, and the grayscale threshold range was adjusted to perform binarization on each image, yielding the total fracture area in each image. The fractures were then skeletonized to determine their total length. The total fracture area divided by the total fracture length was used as the average fracture opening.

[0134] In some alternative embodiments, reference is made to Figure 5 As shown, step S107 above can be implemented in the following way:

[0135] Step S501: Obtain the deep lateral resistivity curve and the shallow lateral resistivity curve;

[0136] Step S501: Based on the deep lateral resistivity curve and the shallow lateral resistivity curve, calculate the cleavage porosity value using the following formula:

[0137]

[0138] In equation (10) above, Φ f The porosity of the formation fracture is expressed in m. f R is the crack bonding index. m R is the resistivity of the drilling fluid filtrate. LLS and R LLD These are the shallow lateral resistivity and deep lateral resistivity of the formation, respectively.

[0139] In some optional embodiments, step S108 above can be implemented in the following manner:

[0140] The azimuth anisotropy characteristics of P-wave seismic attributes are obtained. Based on the azimuth anisotropy characteristics of P-wave seismic attributes and the orientation angle data of P-wave excitation direction relative to fracture strike, the pre-constructed azimuth anisotropy equation is solved.

[0141] The equations for azimuth anisotropy are shown below:

[0142] F(α)=A+Bcos 2α;(11)

[0143] In equation (11) above, α represents the orientation angle of the P-wave excitation direction relative to the fracture strike; A represents the offset factor related to the offset distance; B represents the modulation factor related to the offset distance and fracture characteristics; F(α) is the azimuth anisotropy characteristic of the P-wave seismic properties.

[0144] The density of the fracture development zone is calculated based on the values ​​of the offset factor related to the offset distance and the modulation factor related to the offset distance and fracture characteristics. Specifically, the density of the fracture development zone is quantitatively calculated through the proportional relationship between the B / A value and the fracture density.

[0145] In some optional embodiments, the reservoir space of the target reservoir is quantitatively evaluated based on a first volume percentage, a second volume percentage, a third volume percentage, a fourth volume percentage, a fifth volume percentage, an average aperture, a cleavage porosity value, and a development zone density, including:

[0146] (1) Quantitatively evaluate the pore structure of the target reservoir using the first volume percentage, second volume percentage, third volume percentage, fourth volume percentage, and fifth volume percentage;

[0147] (2) Quantitatively evaluate the fracture structure of the target reservoir by average opening degree;

[0148] (3) Quantitatively evaluate the porosity of the target reservoir by using the cleavage porosity value;

[0149] (4) Quantitatively evaluate the development zone structure of the target reservoir by development zone density.

[0150] Based on the process of steps S101-S109 and combined with geophysical characterization methods, the embodiments of the present invention can obtain a quantitative evaluation method for deep coal and gas reservoir space in complex superimposed basins, as shown in Table 1 below. As can be seen from Table 1, small-angle scattering test, weighted processing of repeated intervals [50nm~100nm], high-pressure mercury injection test, and weighted processing of repeated intervals [1000nm~2000nm] can characterize reservoir pore space. Micron-scale CT scanning test can characterize both reservoir pore space and reservoir fracture space. Stereomicroscopy, dual-lateral resistivity model, and seismic P-wave azimuth / angle information characterize reservoir fracture space.

[0151] Table 1:

[0152]

[0153] Example 2

[0154] Embodiment 2 of the present invention provides a specific implementation process of a quantitative evaluation method for deep coal and rock gas reservoir space, which differs from Embodiment 1 in that the process of calculating the density of the development zone in step S108 is different.

[0155] In some optional embodiments, azimuth anisotropy (AVO) and AVO techniques are fused, and the use of P-wave azimuth and angular information is more conducive to coal seam lithology analysis. Therefore, before solving the azimuth anisotropy equation, the azimuth anisotropy and AVO techniques need to be fused. Specifically, refer to... Figure 6 As shown, this can be achieved in the following way:

[0156] Step S601: Extract data from N azimuth gathers from the profile of the target reservoir, process the data of the N azimuth gathers to obtain the corresponding azimuth migration data volumes; the azimuth migration data volumes include the values ​​of seismic attributes such as amplitude, velocity, and frequency;

[0157] Step S602: From N azimuth gathers, extract data from M azimuth / angle gathers according to a preset incident angle range. For the data from the M azimuth / angle gathers, obtain the corresponding azimuth / angle data volumes respectively. The azimuth / angle data volumes include the values ​​of seismic attributes such as amplitude, velocity, and frequency.

[0158] Step S603: Based on N azimuth migration data volumes and M azimuth / angle data volumes, obtain seismic attribute parameter data related to fracture density; there are multiple seismic attribute parameters; seismic attribute parameters include, but are not limited to, amplitude, velocity, and frequency;

[0159] Step S604: Using seismic attribute fusion technology, normalize the data of each seismic attribute parameter to obtain the azimuth anisotropy characteristics of the fused seismic attributes.

[0160] Specifically, seismic attribute fusion is performed using the following formula:

[0161] Y = a1y1 + a2y2 + a3y3 + ...; (12)

[0162] In equation (12) above, a1, a2, and a3 are the weights of the earthquake attributes; y1, y2, and y3 are the values ​​of the earthquake attributes.

[0163] Accordingly, the solution of the azimuth anisotropy equation is based on the azimuth anisotropy characteristics of the fused seismic attributes. That is, the azimuth anisotropy characteristics of the fused seismic attributes calculated based on formula (12) are input into the above formula (11), and formula (11) is solved.

[0164] The quantitative evaluation method for deep coal and gas reservoirs provided in this invention, combined with geophysical interpretation, can characterize different structures of deep coal and gas reservoirs, such as... Figure 7 As shown.

[0165] Based on the same inventive concept, embodiments of the present invention also provide a quantitative evaluation device for deep coal and rock gas storage space, the structure of which is as follows: Figure 8 As shown, it includes:

[0166] The first measurement module is used to measure the volume percentage of pores in the target reservoir whose diameter is within the first pore diameter range;

[0167] The second measurement module is used to measure the percentage of pore volume in the target reservoir whose inner diameter is located within the second pore diameter range; the second pore diameter range partially overlaps with the first pore diameter range.

[0168] The third measurement module is used to measure the volume percentage of pores in the target reservoir whose diameter is located in the third pore diameter range, and to obtain the third volume percentage; the third pore diameter range partially overlaps with the second pore diameter range, and the third pore diameter range does not overlap with the first pore diameter range;

[0169] The first calculation module is used to calculate a fourth volume percentage based on the first volume percentage and the second volume percentage. The fourth volume percentage represents the volume percentage of pores whose diameters are located in the overlapping part of the second pore diameter range and the first pore diameter range.

[0170] The second calculation module is used to calculate the fifth volume percentage based on the second volume percentage and the third volume percentage. The fifth volume percentage represents the volume percentage of pores whose diameters are located in the overlapping part of the third pore diameter range and the second pore diameter range.

[0171] The fourth measurement module is used to measure the average opening of fractures with a length greater than a preset length within the target reservoir.

[0172] The third calculation module is used to calculate the cleavage porosity value of the target reservoir.

[0173] The fourth calculation module is used to calculate the development zone density of the target reservoir;

[0174] The quantitative evaluation module is used to quantitatively evaluate the reservoir space of the target reservoir based on the percentage of the number and volume of pores with diameters in the first pore diameter range, the percentage of the number and volume of pores with diameters in the second pore diameter range, the percentage of the number and volume of pores with diameters in the third pore diameter range, the average aperture, the cleavage porosity value, and the density of the development zone.

[0175] Regarding the quantitative evaluation device for deep coal and rock gas storage space in the above embodiments, the specific operation methods of each module have been described in detail in the embodiments of the relevant method, and will not be elaborated here.

[0176] Unless otherwise specifically stated, terms such as processing, calculation, operation, determination, display, etc., may refer to the actions and / or processes of one or more processing or computing systems or similar devices that represent the manipulation and conversion of data representing physical (e.g., electronic) quantities within the registers or memory of the processing system into other data similarly representing physical quantities within the memory, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals can be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, symbols, and chips mentioned throughout the above description can be represented by voltage, current, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0177] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.

[0178] In the detailed description above, various features are combined together in a single embodiment to simplify this disclosure. This approach to disclosure should not be construed as reflecting an intention that embodiments of the claimed subject matter require more features than are explicitly stated in each claim. Rather, as reflected in the appended claims, the invention is presented with fewer features than all of the features in a single disclosed embodiment. Therefore, the appended claims are hereby explicitly incorporated into the detailed description, with each claim representing a separate preferred embodiment of the invention.

[0179] Those skilled in the art will also understand that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in alternative ways for each specific application; however, such implementation decisions should not be construed as departing from the scope of this disclosure.

[0180] The steps of the methods or algorithms described in conjunction with the embodiments herein can be directly embodied in hardware, software modules executed by a processor, or a combination thereof. The software modules can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. Alternatively, the processor and storage medium can exist as discrete components in the user terminal.

[0181] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. This software code can be stored in memory units and executed by a processor. The memory units can be implemented within the processor or outside the processor; in the latter case, they are communicatively coupled to the processor via various means, as is well known in the art.

[0182] The foregoing description includes examples of one or more embodiments. It is certainly impossible to describe all possible combinations of components or methods in order to describe the above embodiments, but those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. Furthermore, the term "comprising" as used in the specification or claims is interpreted in a manner similar to the term "including," as interpreted when used as a conjunction in the claims. Additionally, the use of any term "or" in the specification of the claims is intended to mean "non-exclusive or."

Claims

1. A quantitative evaluation method for deep coal and rock gas reservoir space, characterized in that, include: The first volume percentage is obtained by measuring the volume percentage of pores in the target reservoir whose diameter falls within the first pore diameter range; The volume percentage of pores whose inner diameter falls within the second pore diameter range of the target reservoir is measured to obtain the second volume percentage; the second pore diameter range partially overlaps with the first pore diameter range, and the maximum value of the second pore diameter range is greater than the maximum value of the first pore diameter range; The volume percentage of pores whose inner diameter is located within the third pore diameter range of the target reservoir is measured to obtain the third volume percentage; the third pore diameter range partially overlaps with the second pore diameter range, the third pore diameter range does not overlap with the first pore diameter range, and the maximum value of the third pore diameter range is greater than the maximum value of the second pore diameter range; Based on the first volume percentage and the second volume percentage, a fourth volume percentage is calculated, which represents the volume percentage of pores whose diameter is located in the overlapping part of the second pore diameter range and the first pore diameter range. Based on the second volume percentage and the third volume percentage, a fifth volume percentage is calculated, which represents the volume percentage of pores whose diameters are located in the overlapping portion of the third pore diameter range and the second pore diameter range. Measure the average opening of fractures with a length greater than a preset length within the target reservoir; Calculate the cleavage porosity value of the target reservoir; Calculate the development zone density of the target reservoir; The reservoir space of the target reservoir is quantitatively evaluated based on the first volume percentage, the second volume percentage, the third volume percentage, the fourth volume percentage, the fifth volume percentage, the average opening, the cleavage porosity value, and the development zone density.

2. The method as described in claim 1, characterized in that, Based on the first volume percentage and the second volume percentage, the fourth volume percentage is calculated, including: Based on the first volume percentage and the second volume percentage, as well as the preset first weighting coefficient and second weighting coefficient, the fourth volume percentage is calculated using the following formula: In the above formula, V1 represents the fourth volume percentage; f1 represents the first volume percentage; f1 represents the first weighting coefficient; V2 represents the second volume percentage; f2 represents the second weighting coefficient. The first weighting coefficient represents the proportion of pores whose diameters are located in the overlapping portion of the second pore diameter range and the first pore diameter range, to pores whose diameters are located in the first pore diameter range. The second weighting coefficient represents the proportion of pores whose diameter is located in the overlapping part of the second pore diameter range and the first pore diameter range, to the pores whose diameter is located in the second pore diameter range.

3. The method as described in claim 1, characterized in that, Based on the second volume percentage and the third volume percentage, the fifth volume percentage is calculated, including: Based on the second volume percentage and the third volume percentage, as well as the preset third weighting coefficient and fourth weighting coefficient, the fifth volume percentage is calculated using the following formula: In the above formula, V1 represents the fourth volume percentage; V2 represents the second volume percentage; f3 represents the third weighting coefficient; V3 represents the third volume percentage; f4 represents the fourth weighting coefficient; The third weighting coefficient represents the proportion of pores whose diameter is located in the overlapping part of the third pore diameter range and the second pore diameter range, to the pores whose diameter is located in the second pore diameter range. The fourth weighting coefficient represents the proportion of pores whose diameter is located in the overlapping part of the third pore diameter range and the second pore diameter range, to the pores whose diameter is located in the third pore diameter range.

4. The method as described in claim 1, characterized in that, The first volume percentage is obtained by measuring the volume percentage of pores in the target reservoir whose diameter falls within the first pore diameter range, including: Samples are prepared from the target reservoir according to a preset size, the samples are dried, and the scattering images of all samples after drying are obtained. Based on the scattering geometry, the curve of the relationship between scattering intensity and scattering angle corresponding to the scattering image is obtained. The first volume percentage is obtained by solving the curve of the relationship between scattering intensity and scattering angle.

5. The method as described in claim 1, characterized in that, Based on the first volume percentage, the second volume percentage, the third volume percentage, the fourth volume percentage, the fifth volume percentage, the average aperture, the cleavage porosity value, and the development zone density, the reservoir space of the target reservoir is quantitatively evaluated, including: The pore structure of the target reservoir is quantitatively evaluated using the first volume percentage, the second volume percentage, the third volume percentage, the fourth volume percentage, and the fifth volume percentage. The fracture structure of the target reservoir is quantitatively evaluated using the average aperture. The porosity of the target reservoir is quantitatively evaluated using the cleavage porosity value. The development zone structure of the target reservoir is quantitatively evaluated by development zone density.

6. The method as described in claim 1, characterized in that, The calculation of the cleavage porosity value of the target reservoir includes: Obtain the deep lateral resistivity curve and the shallow lateral resistivity curve; Based on the deep lateral resistivity curve and the shallow lateral resistivity curve, the cleavage porosity value is calculated using the following formula: In the above formula, Φ f The porosity of the formation fracture is expressed in m. f R is the crack cementation index. m R is the resistivity of the drilling fluid filtrate. LLS and R LLD These are the shallow lateral resistivity and deep lateral resistivity of the formation, respectively.

7. The method as described in claim 1, characterized in that, The calculation of the development zone density of the target reservoir includes: The azimuth anisotropy characteristics of P-wave seismic attributes are obtained. Based on the azimuth anisotropy characteristics of the P-wave seismic attributes and the orientation angle data of the P-wave excitation direction relative to the fracture strike, the pre-constructed azimuth anisotropy equation is solved. The azimuth anisotropy equation is as follows: F(α) = A + Bcos2α; In the above formula, α represents the orientation angle of the P-wave excitation direction relative to the fracture strike; A represents the offset factor related to the offset distance; B represents the modulation factor related to the offset distance and fracture characteristics; F(α) is the azimuth anisotropy characteristic of the P-wave seismic properties. The development zone density is calculated based on the values ​​of the offset factor related to the offset distance and the modulation factor related to the offset distance and the fracture characteristics.

8. The method as described in claim 7, characterized in that, Before solving the azimuth anisotropy equation, the following steps are also included: Data from N azimuth gathers are extracted from the profile of the target reservoir. The data from the N azimuth gathers are processed to obtain the corresponding azimuth offset data volumes. From the N azimuth gathers, extract data from M azimuth / angle gathers according to a preset incident angle range, and obtain the corresponding azimuth / angle data volumes from the data of the M azimuth / angle gathers respectively; Based on N azimuth offset data volumes and M azimuth / angle data volumes, seismic attribute parameter data related to fracture density are obtained; there are multiple seismic attribute parameters. Seismic attribute fusion technology is used to normalize the seismic attribute parameter data of each of the above-mentioned seismic attributes to obtain the azimuth anisotropy characteristics of the fused seismic attributes. Accordingly, the solution to the azimuth anisotropy equation is based on the azimuth anisotropy characteristics of the fused seismic attributes.

9. A quantitative evaluation device for deep coal and rock gas storage space, characterized in that, include: The first measurement module is used to measure the volume percentage of pores in the target reservoir whose diameter is within the first pore diameter range; The second measurement module is used to measure the percentage of pore volume in the target reservoir whose inner diameter is located within the second pore diameter range; the second pore diameter range partially overlaps with the first pore diameter range; The third measurement module is used to measure the volume percentage of pores in the target reservoir whose diameter is located within the third pore diameter range, and to obtain the third volume percentage; the third pore diameter range partially overlaps with the second pore diameter range, and the third pore diameter range does not overlap with the first pore diameter range; The first calculation module is used to calculate a fourth volume percentage based on the first volume percentage and the second volume percentage, wherein the fourth volume percentage represents the volume percentage of pores whose diameter is located in the overlapping part of the second pore diameter range and the first pore diameter range. The second calculation module is used to calculate a fifth volume percentage based on the second volume percentage and the third volume percentage, wherein the fifth volume percentage represents the volume percentage of pores whose diameter is located in the overlapping part of the third pore diameter range and the second pore diameter range. The fourth measurement module is used to measure the average opening of fractures with a length greater than a preset length within the target reservoir; The third calculation module is used to calculate the cleavage porosity value of the target reservoir. The fourth calculation module is used to calculate the development zone density of the target reservoir; The quantitative evaluation module is used to quantitatively evaluate the reservoir space of the target reservoir based on the percentage of the number and volume of pores with diameters in the first pore diameter range, the percentage of the number and volume of pores with diameters in the second pore diameter range, the percentage of the number and volume of pores with diameters in the third pore diameter range, the average aperture, the cleavage porosity value, and the development zone density.

10. A computer storage medium, characterized in that, The computer storage medium stores computer-executable instructions, which, when executed by a processor, implement the quantitative evaluation method for coal and rock gas storage space as described in any one of claims 1-8.

11. A terminal device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the quantitative evaluation method for coalbed methane reservoir space as described in any one of claims 1-8.

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