A seismic inversion method for lithology and pore structure parameters of a tight formation

Abstract

This invention belongs to the field of oil and gas geophysical exploration technology, and relates to a seismic inversion method for lithological and pore structure parameters of tight strata. It includes establishing lithological parameters (LI) and pore structure parameters (MP) that can effectively identify lithology and pore structure through elastic parameter combination and coordinate rotation methods, and establishing a generalized AVO equation regarding lithological parameters, pore structure parameters, and density. The method uses elastic impedance inversion to predict these reservoir parameters from pre-stack seismic data. Furthermore, it proposes a combination factor F combining LI, MP, and elastic modulus K for comprehensive characterization of the physical properties of tight reservoirs. This seismic inversion method for lithological and pore structure parameters of tight strata can directly predict lithological and pore structure parameters from seismic data. The constructed combination factor F can predict high-gas-bearing and high-porosity / permeability high-quality reservoirs, providing important information for the prediction of tight sandstone gas reservoirs.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas geophysical exploration technology, specifically relating to a seismic inversion method for the lithology and pore structure parameters of tight strata. Background Technology

[0002] Unconventional tight sandstone is a type of rock with a reservoir caprock permeability of less than 0.1 mD. Tight sandstone gas typically refers to natural gas in such reservoirs. Tight sandstone reservoirs are characterized by their dense lithology, strong heterogeneity, low porosity, and low permeability, characteristics that severely impact the economic viability of tight sandstone gas development. The exploration and development of tight sandstone gas relies on utilizing high-precision seismic methods to predict areas rich in high-porosity, high-permeability natural gas.

[0003] Lithology and pore structure prediction are two crucial aspects of tight sandstone reservoir research. The accuracy of lithology identification directly impacts the reliability of reservoir evaluation results during comprehensive assessment. However, tight sandstone reservoirs present significant challenges due to their complex pore structure and strong heterogeneity. The pore structure of tight sandstone reservoir rocks directly determines the reservoir's storage capacity and permeability, significantly influencing reservoir evaluation and oil and gas recovery. In reality, the minerals, pores, and fluids in rocks are highly complex. Different mineral contact relationships and actual geological activity in the formation can lead to complex pore structures, posing significant challenges to subsequent reservoir prediction and fluid identification. Regarding rock physics modeling of tight sandstone, Ruiz and Cheng (2010) proposed a soft porosity model using the Berryman self-compatible model to address microfractures in low-porosity, low-permeability tight sandstone and applied it to calculate rock physics elastic parameters. Yin Xingyao et al. (2016) proposed a method for constructing a rock physics model suitable for tight porous fractured reservoirs, taking into account the characteristics of low porosity, low permeability, and microfracture development in tight sandstone reservoirs. Well logging data plays a crucial role in well logging reservoir evaluation, rock physics experiments, and seismic reservoir prediction. As a bridge linking these three aspects, the flexible application of well logging data can lay a solid foundation for a comprehensive understanding of reservoirs. Garder et al. (1974) established a connection between well logging data and seismic data by studying the relationship between well logging data and wave velocity. Xu S. and White R.E. (1995) established the relationship between clay content, porosity, pore aspect ratio, and P-wave and S-wave velocities using a rock physics model. In recent years, using seismic information to predict lithology and fractures has also become a research hotspot. Mallick et al. (1998) pioneered the use of AVOZ data to invert the elastic parameters of fractured media. Bachrach et al. (2006, 2009) proposed to complete the pre-stack seismic inversion of the elastic parameters and fracture parameters of fractured reservoirs by reconstructing the elastic parameters and anisotropic parameters of fractured reservoirs.

[0004] If the parameters of lithology and pore structure can be identified, a new AVO formula can be established, and the above parameters can be predicted directly from pre-stack seismic data using the seismic impedance inversion method. This is a new attempt that can provide important information for the prediction of tight sandstone gas reservoirs. Summary of the Invention

[0005] The purpose of this invention is to provide a seismic inversion method for the lithology and pore structure parameters of tight strata, so as to solve the problem of predicting lithology and pore structure from seismic data and obtaining the combination factor F that can predict high-gas-bearing and high-porosity-permeability high-quality reservoirs, thus providing valuable information for the prediction of tight sandstone gas reservoirs.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] This invention derives parameters LI and MP, which characterize lithology and pore structure, through elastic parameter combination and coordinate rotation methods. A seismic elastic AVO expression is constructed to directly predict the elastic parameters characterizing tight sandstone gas reservoirs, including LI (lithology) and MP (pore structure). Furthermore, well logging data analysis and comparison verify the sensitivity of LI and MP in identifying the lithology and pore structure of tight sandstone gas reservoirs. Finally, a combination factor F, combining parameters LI, MP, and the elastic modulus K, is proposed. This invention can directly predict lithology and pore structure from seismic data, and the resulting combination factor F can predict high-porosity, high-permeability, high-gas-bearing target reservoirs, providing valuable information for the prediction of tight sandstone gas reservoirs.

[0008] A seismic inversion method for lithology and pore structure parameters of tight strata includes the following steps:

[0009] Step A: Obtain pre-stack seismic data for the study area and construct pre-stack corner gathers;

[0010] Step B: Obtain the lithological parameter LI(θ) and pore size parameter MP(θ) through elastic parameter combination and coordinate rotation; use well logging data to find the relationship between LI(θ) and MP(θ) and parameter GR / V. P 2 and φ×φ f The angle θ at which the two have the highest correlation max1 With θ max2 The parameters LI and MP, used to characterize lithology and pore structure, are obtained, where θ is the rotation angle, GR is the natural gamma value from well logging, and V... P Where φ is the longitudinal wave velocity and φ is the porosity. f For microcrack porosity;

[0011] Step C: Derive the new seismic elastic AVO equations for LI and MP;

[0012] Step D: Based on the AVO equation in step C, establish an elastic impedance inversion method to directly predict reservoir parameters LI and MP, which are then applied to the detection of favorable lithology and high porosity and permeability zones in tight sandstone gas reservoirs.

[0013] Step E: Combine LI, MP and elastic modulus K to construct combination factor F, and comprehensively predict favorable tight sandstone gas reservoirs;

[0014] Step F: Apply well logging data to calibrate the inversion results and verify the accuracy and reliability of the constructed LI, MP, and F for predicting tight sandstone gas reservoirs.

[0015] Furthermore, in step B, the parameters LI and MP, which characterize the lithology and pore structure, are obtained through the combination of elastic parameters and coordinate rotation, namely:

[0016] LI = I P -c1I S

[0017] MP = I P -c2I S

[0018] Among them, I P and I S c1 and c2 are the impedances of the longitudinal and transverse waves, respectively, and scale factors.

[0019] Furthermore, in step C, the seismic elastic AVO formula constructed using lithological parameter LI, pore structure parameter MP, and density ρ is expressed as follows:

[0020]

[0021] Among them, V P and V S The P-wave and S-wave velocities of saturated rock are given by c1, c2, and V, respectively. P and V S The relevant parameters are: ρ is the density of the underground rock, ΔLI is the difference between the parameters LI on both sides of the interface, ΔMP is the difference between the parameters MP on both sides of the interface, Δρ is the difference between the densities on both sides of the interface, and θ is the angle of incidence.

[0022] Furthermore, in step D, the reservoir parameters LI and MP are directly inverted using elastic impedance, as shown in the following formula:

[0023]

[0024] Where a(θ), b(θ), and c(θ) are coefficients related to the incident angle, respectively:

[0025]

[0026]

[0027]

[0028] Furthermore, θ1, θ2, and θ3 represent the near, middle, and far incident angles, respectively.

[0029] Compared with the prior art, the beneficial effects of the present invention are:

[0030] This invention proposes parameters for identifying lithology and pore structure, establishes a new AVO formula, and applies a seismic impedance inversion method to directly predict these parameters from pre-stack seismic data. Specifically, it uses elastic parameter combination and coordinate rotation methods to establish the lithology parameter LI and pore structure parameter MP and GR / V from well logging data. P 2 and φ×φ f The relationship between the parameters LI and MP is established; a reflection coefficient equation with LI, MP and density is established; parameters LI and MP are obtained by direct inversion using elastic impedance data; finally, combined with the bulk modulus K which can represent the natural gas content, a combination factor F that can effectively identify tight sandstone gas reservoirs and natural gas enrichment is proposed; the results can directly predict target reservoirs with high gas content and high porosity and permeability, providing valuable information for the prediction of tight sandstone gas reservoirs. Attached Figure Description

[0031] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a flowchart illustrating the implementation of the seismic inversion method for lithology and pore structure parameters of tight strata.

[0033] Figure 2 It is the correlation coefficient under varying rotation angle θ;

[0034] Figure 3 Using GR / V P 2 As a color mark in θ max = at 80° I P Intersection diagram with LI;

[0035] Figure 4 Using φ×φ f As a color mark in θ max =45° I P Intersection diagram with LI;

[0036] Figure 5 This is a post-stack seismic profile of the AE wells in the study area in the embodiment;

[0037] Figure 6 This is a well-connected profile of the parameter LI inversion results of the AE well in the study area in the embodiment;

[0038] Figure 7 This is a well-connected profile of the parameter MP inversion results of the AE well in the study area in the embodiment;

[0039] Figure 8 This is a well-connected cross-sectional view of the elastic modulus K of well AE in the study area in the embodiment;

[0040] Figure 9 This is a well-connected profile diagram of the combination factor F of the AE wells in the study area in the embodiment. Detailed Implementation

[0041] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0042] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0043] This invention proposes a seismic inversion method for lithology and pore structure parameters of tight formations. Specifically, it obtains parameters LI and MP, which characterize lithology and pore structure, through elastic parameter combination and coordinate rotation methods. A seismic elastic AVO expression is then constructed to directly predict the elastic parameters characterizing tight sandstone gas reservoirs, including LI (lithology) and MP (pore structure). Furthermore, through well logging data analysis and comparison, the sensitivity of LI and MP to the identification of lithology and pore fractures in tight sandstone gas reservoirs is verified. Finally, a combination factor F, combining LI, MP, and the elastic modulus K, is proposed. This invention can directly predict lithology and pore structure from seismic data, and the resulting combination factor F can predict high-gas-bearing and high-porosity / permeability high-quality reservoirs, providing valuable information for the prediction of tight sandstone gas reservoirs.

[0044] In this embodiment, as Figure 1 As shown, the specific implementation scheme of the present invention to achieve the above objectives is as follows:

[0045] Step 1: Obtain pre-stack seismic data for the study area and construct pre-stack angle gathers.

[0046] Step 2: Obtain the lithological parameter LI(θ) and the pore size parameter MP(θ) through elastic parameter combination and coordinate rotation, where θ is the rotation angle. Use well logging data to find the relationship between LI(θ) and MP(θ) and the parameter GR / V. P 2 and φ×φ f The angle θ at which the two have the highest correlation max1 With θ max2 The parameters LI and MP, used to characterize lithology and pore structure, were obtained. Here, GR is the natural gamma ray value from well logging, and V... P Where φ is the longitudinal wave velocity and φ is the porosity. f This refers to the porosity of microcracks. Figure 2 When θ is 80° and 45° respectively, there is a large correlation between groups, and LI and MP are obtained at this time:

[0047] LI = I P -c1I S (1)

[0048] MP = I P -c2I S (2)

[0049] in I P In the intersection plot with LI, a high LI value corresponds to GR / V. P 2 The low value indicates that parameter LI can effectively identify lithology, such as... Figure 3 As shown. Furthermore, the parameter MP can be effectively determined based on φ×φ f Value-based identification of pore structures, where low MP values ​​correspond to φ×φ f The value is relatively high, such as Figure 4 As shown. Therefore, MP parameters can be used for the identification of permeable zones in tight formations.

[0050] By using the coordinate rotation method to calculate the combination of elastic parameters at different angles, the lithological parameter LI(θ) and the pore fracture parameter MP(θ) are obtained. The parameter GR / V, calculated from the combination of elastic parameters and well logging data, is then sought. P 2 and φ×φ f The angle at which the maximum correlation occurs, and the combination of elastic parameters at this angle, are the parameters LI and MP that can characterize lithology and pore structure.

[0051] Step 3: Derive the new seismic elastic AVO equations for parameters LI and MP.

[0052] According to formulas (1) and (2), we can obtain:

[0053]

[0054]

[0055] definition

[0056]

[0057]

[0058] Substitute formulas (5)-(6) into formulas (3)-(4)

[0059]

[0060]

[0061] Formulas (7)-(8) can be further converted to

[0062]

[0063]

[0064] In the Fatti equations, the AVO theory formula is:

[0065]

[0066] Substituting formulas (9) and (20) into formula (11), we get...

[0067]

[0068] Formula (12) is a new seismic elastic AVO expression containing parameters LI, MP and density.

[0069] Step 4: Based on the AVO equation in Step 3, establish an elastic impedance inversion method to directly predict reservoir parameters LI and MP, which are then applied to the detection of favorable lithology in tight sandstone gas reservoirs and high porosity and permeability zones, respectively.

[0070] According to the elastic impedance reversal theory proposed by Connolly (1999), the P-wave reflection coefficient R PP The relationship between (θ) and elastic impedance EI(θ) can be expressed in a form similar to that of acoustic impedance:

[0071]

[0072] Where EI1(θ) and EI2(θ) are the elastic impedances of the upper and lower media at the reflecting interface, and ΔEI(θ) is the difference and average value of the two.

[0073] Substituting formula (12) into formula (13), we can integrate both sides simultaneously and exponentialize them:

[0074] EI(θ)=LI a(θ) MP b(θ) ρ c(θ) (14)

[0075] in

[0076]

[0077]

[0078]

[0079] To make the size of the elastic impedance data volume the same as the acoustic impedance, formula (14) is normalized according to the elastic impedance normalization method proposed by Whitcombe (2002):

[0080]

[0081] Where LI0, PMI0, and ρ0 are the average values ​​of the well logging data; EI0 is the elastic impedance normalization factor, which can be expressed as:

[0082]

[0083] Take the natural logarithm of both sides of equation (19) after dividing by EI0.

[0084]

[0085] The resulting system of equations:

[0086]

[0087] Based on the elastic impedance inversion method, the reflection coefficient R can be established. PP The relationship between (θ) and elastic impedance EI(θ) is used to directly invert reservoir parameters LI and MP using seismic data.

[0088] Step 5: Combine LI, MP and elastic modulus K to construct a combination factor F, and comprehensively predict favorable tight sandstone gas reservoirs.

[0089]

[0090] The elastic modulus K can be used to characterize gas-bearing tight sandstone because it is affected by the gas content of the tight sandstone. Therefore, by combining the parameters LI, MP, and the elastic modulus K (which characterizes gas content) to construct a combination factor F, we can directly predict high-porosity, high-permeability, and high-gas-bearing areas, i.e., comprehensively predict favorable gas reservoirs in tight sandstone.

[0091] Step 6: Apply well logging data to calibrate and invert the results, and verify the effectiveness and reliability of the parameters LI, MP, and F constructed in this invention for identifying high-porosity and high-permeability gas-bearing areas in tight sandstone gas reservoirs.

[0092] Figure 6 and Figure 7 This is a well profile diagram showing the inversion results of parameters LI and MP in the study area obtained using the new AVO formula. It can be seen that parameter LI matches the well logging GR data, allowing for the differentiation of sandstone and mudstone formations. Parameter MP matches the well logging permeability data curves and can be used as a parameter to identify pore and fracture structures. Figure 8 This is a well-connected profile of the elastic modulus K in the study area. Figure 9 This is a well profile diagram with the combination factor F. The diagram shows that F can identify tight sandstone gas reservoirs with high porosity, permeability, and gas content, providing an effective method for predicting favorable tight sandstone gas reservoirs.

[0093] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A seismic inversion method for determining lithology and pore structure parameters of a compacted formation, characterized by, Includes the following steps: Step A: Obtain pre-stack seismic data for the study area and construct pre-stack corner gathers; Step B: Obtain the lithological parameter LI(θ) and pore structure parameter MP(θ) through elastic parameter combination and coordinate rotation; use well logging data to find the relationship between LI(θ) and MP(θ) and parameter GR / V. P 2 and φ×φ f The angle θ at which the two have the highest correlation max1 With θ max2 The lithological parameter LI and pore structure parameter MP, used to characterize lithology and pore structure, are obtained, where θ is the rotation angle, GR is the natural gamma ray value from well logging, and V... P Where φ is the longitudinal wave velocity and φ is the porosity. f For microcrack porosity; Step C: Derive the new seismic elastic AVO equations for lithological parameter LI and pore structure parameter MP; Step D: Based on the AVO equation in step C, establish an elastic impedance inversion method to directly predict reservoir lithology parameter LI and pore structure parameter MP, which are then applied to the detection of favorable lithology and high porosity and permeability zones in tight sandstone gas reservoirs. Step E: Combine LI, MP and elastic modulus K to construct combination factor F, and comprehensively predict favorable tight sandstone gas reservoirs; Step F: Apply well logging data to calibrate the inversion results and verify the accuracy and reliability of the constructed lithological parameter LI, pore structure parameter MP, and combination factor F for predicting tight sandstone gas reservoirs. In step B, the parameters LI and MP, which characterize lithology and pore structure, are obtained through elastic parameter combination and coordinate rotation, namely: LI = I P - cl I S MP = I P - c2I S where I P and I S are the longitudinal and shear wave impedances, and c1 and c2 are scale factors. In step C, the seismic elastic AVO formula constructed using lithological parameter LI, pore structure parameter MP, and density ρ is expressed as follows: ； Among them, V P and V S The P-wave and S-wave velocities of saturated rock are given by c1, c2, and V, respectively. P and V S The relevant parameters are: ρ is the density of the underground rock, ΔLI is the difference between the parameters LI on both sides of the interface, ΔMP is the difference between the parameters MP on both sides of the interface, Δρ is the difference between the densities on both sides of the interface, and θ is the angle of incidence. In step D, the reservoir lithology parameter LI and pore structure parameter MP are directly inverted using elastic impedance, and the formula is as follows: ； Where a(θ), b(θ), and c(θ) are coefficients related to the incident angle, respectively: ； Furthermore, θ1, θ2, and θ3 represent the near, middle, and far incident angles, respectively.

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