Hybrid Impedance Sandbody Identification Method Based on Prestack Quasi-Shear-Wave Reflectivity Attributes

Abstract

The present invention discloses a method for identifying hybrid impedance sand bodies based on pre-stack pseudo-S-wave reflectivity attributes, belonging to the field of petroleum exploration. The method for identifying hybrid impedance sand bodies includes: determining the impedance type of the sand body; based on the impedance type of the sand body, determining the seismic response characteristics of the sand body through well-seismic calibration; based on the seismic response characteristics of the sand body, applying pre-stack seismic angle gather data to perform AVO attribute inversion to obtain P-G pseudo-S-wave reflectivity attributes; respectively calculating the root mean square amplitude of the P-G pseudo-S-wave reflectivity attributes and the original seismic data, and performing amplitude normalization on the obtained root mean square amplitude; performing amplitude addition calculation on the amplitude-normalized root mean square amplitude to obtain a fused attribute volume; extracting the amplitude value of the fused attribute volume by using high-density isochronal slices based on global automatic volume tracking, and depicting the planar distribution of the sand body according to the amplitude value of the fused attribute volume. The present invention improves the accuracy of sand body identification.

Description

Technical Field

[0001] The present invention belongs to the field of oil exploration, and relates to the technology of sand body identification and characterization in the field of seismic data interpretation in oil exploration. In particular, it relates to a method for identifying hybrid impedance sand bodies based on pre-stack pseudo-shear wave reflectivity attributes. Background Art

[0002] The three-dimensional seismic identification of sand body distribution characteristics is based on the impedance difference between the sand body and the surrounding rock. When the impedance value of the sand body is lower than that of the surrounding rock, the sand body shows "top valley bottom peak bright spot reflection", and when the impedance value of the sand body is higher than that of the surrounding rock, the sand body shows "top peak bottom valley bright spot reflection". Based on this seismic response characteristic of the sand body, the planar characterization of the sand body is completed by extracting the root mean square amplitude stratigraphic slice.

[0003] The existing techniques for sand body characterization using post-stack seismic attribute analysis have the following problems and disadvantages:

[0004] 1. Conventional post-stack seismic data can only characterize high-impedance and low-impedance sand bodies with large impedance differences from the surrounding rock, and have weak identification ability for sand bodies with small impedance differences from the surrounding rock and unremarkable seismic reflection bright spots.

[0005] 2. Affected by factors such as burial depth, provenance direction, and diagenetic evolution stage, sand bodies of the same period may show characteristics of high P-wave impedance, medium P-wave impedance, and low P-wave impedance. Conventional seismic attributes cannot effectively characterize the distribution of sand bodies.

[0006] 3. Conventional stratigraphic slices are equal-proportion slices, which are relatively isochronous. When the sedimentation thickness changes, the isochronism of the equal-proportion slices is poor, and the accuracy of sand body characterization is reduced. Summary of the Invention

[0007] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a method for identifying hybrid impedance sand bodies based on pre-stack pseudo-shear wave reflectivity attributes.

[0008] The purpose of the present invention is achieved by the following technical solutions: A method for identifying hybrid impedance sand bodies based on pre-stack pseudo-shear wave reflectivity attributes, including:

[0009] Determine the impedance type of the sand body;

[0010] Based on the impedance type of the sand body, determine the seismic response characteristics of the sand body through well-seismic calibration;

[0011] Based on the seismic response characteristics of the sand body, apply pre-stack seismic angle gather data for AVO attribute inversion to obtain the P-G pseudo-shear wave reflectivity attribute;

[0012] Calculate the root-mean-square amplitude of the P-G pseudo-SV wave reflectivity attribute and the original seismic data respectively, and perform amplitude normalization on the root-mean-square amplitude of the P-G pseudo-SV wave reflectivity attribute and the root-mean-square amplitude of the original seismic data;

[0013] Perform amplitude addition calculation on the root-mean-square amplitude of the P-G pseudo-SV wave reflectivity attribute and the root-mean-square amplitude of the original seismic data after amplitude normalization to obtain a fused attribute volume;

[0014] Adopt high-density isochronal slices based on global automatic volume tracking to extract the amplitude values of the fused attribute volume, and depict the planar distribution of sand bodies according to the amplitude values of the fused attribute volume.

[0015] Furthermore, the method for obtaining the P-G pseudo-SV wave reflectivity attribute is as follows:

[0016] Based on the pre-stack seismic angle gather data, apply the Aki-Richards equation to obtain the AVO attribute;

[0017] Obtain the intercept and gradient according to the AVO attribute, and perform interpolation on the intercept and gradient to obtain the P-G pseudo-SV wave reflectivity attribute.

[0018] Furthermore, the method for obtaining the root-mean-square amplitude of the original seismic data is as follows:

[0019] Within a given time window, calculate the average value of the sum of the squares of the amplitudes of the original seismic data;

[0020] Take the square root of the average value of the sum of the squares of the amplitudes of the original seismic data to obtain the root-mean-square amplitude of the original seismic data.

[0021] Furthermore, the method for obtaining the root-mean-square amplitude of the P-G pseudo-SV wave reflectivity attribute is as follows:

[0022] Within a given time window, calculate the average value of the sum of the squares of the amplitudes of the P-G pseudo-SV wave reflectivity attribute;

[0023] Take the square root of the average value of the sum of the squares of the amplitudes of the P-G pseudo-SV wave reflectivity attribute to obtain the root-mean-square amplitude of the P-G pseudo-SV wave reflectivity attribute.

[0024] Furthermore, the amplitude normalization of the root-mean-square amplitude of the P-G pseudo-SV wave reflectivity attribute and the root-mean-square amplitude of the original seismic data includes:

[0025] Regularize the value range of the root-mean-square amplitude of the P-G pseudo-SV wave reflectivity attribute and the root-mean-square amplitude of the original seismic data into the same value range space [1 - 10000] through mathematical algorithms respectively.

[0026] Furthermore, the method for extracting the high-density isochronal slices is as follows:

[0027] Establish a relative isochronous framework model based on global automatic body tracking;

[0028] Based on the relative isochronous framework model, extract high-density isochronous interpretation horizon slices according to the required top and bottom windows of the target layer to obtain high-density isochronous slices.

[0029] The beneficial effects of the present invention are:

[0030] (1) The present invention applies the P-G pseudo-S-wave reflectivity attribute to make up for the problem of low accuracy in depicting medium and high impedance sand bodies using conventional seismic attributes, and introduces the method of depicting medium and high impedance sand bodies from post-stack to pre-stack;

[0031] (2) The present invention normalizes and fuses the pseudo-S-wave reflectivity attribute and conventional seismic attributes, and can realize the identification of high, medium, and low P-wave impedance sand bodies on a single attribute;

[0032] (3) The present invention applies the global optimization automatic tracking result to establish isochronous stratigraphic slices, which improves the isochronism of the stratigraphic slices compared with equal-proportion slices, and further improves the accuracy of sand body identification. Description of the Drawings

[0033] Figure 1 It is a flowchart of an embodiment of the method for identifying mixed impedance sand bodies in the present invention;

[0034] Figure 2 It is a synthetic seismogram section in an embodiment;

[0035] Figure 3 It is an original seismic section in an embodiment;

[0036] Figure 4 It is a pseudo-S-wave reflectivity section in an embodiment;

[0037] Figure 5 It is a fused root-mean-square attribute section in an embodiment;

[0038] Figure 6 It is an original seismic root-mean-square amplitude isochronous stratigraphic slice in an embodiment;

[0039] Figure 7 It is a pseudo-S-wave reflectivity root-mean-square amplitude isochronous stratigraphic slice in an embodiment. Detailed Embodiments

[0040] Next, the technical solutions of the present invention will be clearly and completely described in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0041] Refer to Figures 1 to 7 , the present invention provides a method for identifying hybrid impedance sand bodies based on pre-stack pseudo-S-wave reflectivity attributes:

[0042] As Figure 1 shown, the method for identifying hybrid impedance sand bodies based on pre-stack pseudo-S-wave reflectivity attributes includes:

[0043] Step S100. Determine the impedance type of the sand body.

[0044] For example, since there are logging curves for sand bodies after drilling, the sand bodies can be classified according to their impedance characteristics based on a preset classification standard to obtain high, medium, and low impedance classifications.

[0045] Step S200. Based on the impedance type of the sand body, determine the seismic response characteristics of the sand body through well-seismic calibration.

[0046] The well-seismic calibration is the process of obtaining a simulated seismic trace by convolving a wavelet with a seismic reflection coefficient. The mathematical form of the convolution model is:

[0047] X(t) = W(t) * R(t) + N(t)

[0048] In the formula, X(t) represents the seismic record; W(t) is the seismic wavelet; R(t) is the formation reflection coefficient; N(t) is the random environmental noise.

[0049] Specifically, a time-depth table is obtained through well-seismic calibration to complete the matching of the well in the depth domain and the seismic data in the time domain. Among them, the amplitude, phase, and frequency characteristics of the seismic reflection corresponding to the channel sand body after calibration are the seismic response characteristics of the sand body.

[0050] Step S300. Based on the seismic response characteristics of the sand body, apply pre-stack seismic angle gather data for AVO attribute inversion to obtain the P-G pseudo-S-wave reflectivity attribute.

[0051] In one embodiment, the method for obtaining the P-G pseudo-S-wave reflectivity attribute is: based on the pre-stack seismic angle gather data, apply the Aki-Richards equation to obtain the AVO attribute; obtain the intercept and gradient according to the AVO attribute, and interpolate the intercept and gradient to obtain the P-G pseudo-S-wave reflectivity attribute.

[0052] The expression of the Aki-Richards equation is:

[0053]

[0054] R P (θ) ≈ P + Gsin 2 θ + C(tg 2 θ - sin 2 θ)

[0055] In the formula, P represents the intercept, G represents the gradient, C represents the curvature, Vp represents the P-wave velocity, Vs represents the S-wave velocity, ρ represents the density, θ represents the incident angle, and Rp represents the reflection coefficient.

[0056] In this embodiment, when the ratio of the P-wave velocity to the S-wave velocity is approximately equal to 2 (i.e., equal to 2 within the allowable difference range), Vp = 2Vs, and the P-G pseudo-S-wave reflectivity attribute can represent the S-wave impedance characteristic, and Rs = 1 / 2(P - G). The derivation is as follows:

[0057]

[0058]

[0059] In the formula, P represents the intercept, G represents the gradient, and Rs represents the pseudo-S-wave reflectivity.

[0060] Step S400. Calculate the root mean square amplitude of the P-G pseudo-S-wave reflectivity attribute and the original seismic data respectively, and perform amplitude normalization on the root mean square amplitude of the P-G pseudo-S-wave reflectivity attribute and the root mean square amplitude of the original seismic data.

[0061] In one embodiment, the method for calculating the root mean square amplitude of the original seismic data is as follows: within a given time window, calculate the average value of the sum of the squares of the amplitudes of the original seismic data; take the square root of the average value of the sum of the squares of the amplitudes of the original seismic data to obtain the root mean square amplitude of the original seismic data.

[0062] In one embodiment, the method for calculating the root mean square amplitude of the P-G pseudo-S-wave reflectivity attribute is as follows: within a given time window, calculate the average value of the sum of the squares of the amplitudes of the P-G pseudo-S-wave reflectivity attribute; take the square root of the average value of the sum of the squares of the amplitudes of the P-G pseudo-S-wave reflectivity attribute to obtain the root mean square amplitude of the P-G pseudo-S-wave reflectivity attribute.

[0063] Since the root mean square amplitude of the P-G pseudo-S-wave reflectivity attribute and the root mean square amplitude of the original seismic data are very sensitive to particularly large amplitudes, it is easy to identify special rock masses such as bright spots, dark spots, and igneous rocks on the seismic section.

[0064] The derivation calculation formula of the root mean square amplitude is as follows:

[0065]

[0066] In the formula, A rms represents the root mean square amplitude, and x i represents the amplitude.

[0067] In one embodiment, amplitude normalization of the root-mean-square amplitude of the P-G pseudo-S wave reflectivity attribute and the root-mean-square amplitude of the original seismic data includes: respectively regularizing the value ranges of the root-mean-square amplitude of the P-G pseudo-S wave reflectivity attribute and the root-mean-square amplitude of the original seismic data into the same value range space [1 - 10000] through mathematical algorithms.

[0068] Step S500. Perform amplitude addition calculation on the root-mean-square amplitude of the amplitude-normalized P-G pseudo-S wave reflectivity attribute and the root-mean-square amplitude of the original seismic data to obtain a fused attribute volume.

[0069] Step S600. Extract the amplitude values of the fused attribute volume using high-density isochronal slices based on global automatic volume tracking, and depict the planar distribution of sand bodies according to the amplitude values of the fused attribute volume.

[0070] The global optimization automatic tracking technology is as follows: Using the algorithm of the optimization cost function, on the basis of simultaneously considering seismic reflection characteristics, global consistency of formation deposition, sedimentation thickness, formation inheritance and other comprehensive seismic and geological factors, adopting the "global thinking" mode, considering the entire three-dimensional seismic data volume as a whole, the interpretation scheme and interpretation mode are based on the seismic and geological information contained in the entire three-dimensional data volume, and accurately establishing a relative isochronal framework model.

[0071] The expression of the cost function is:

[0072]

[0073] In the formula, P(i) and P(j) represent the coordinates of seismic "volume elements", V i and V j represent the image pixel feature values of seismic "volume elements", N′ represents the total number of "volume elements" of the seismic data, represents the size of the seismic "volume element".

[0074] The high-density isochronal formation slice refers to: a series of high-density isochronal interpretation horizon slices extracted according to the top and bottom windows of the target layer on the basis of the results obtained by global optimization tracking.

[0075] The high-density interpretation horizon slice refers to: each peak, trough, and zero-phase point in the vertical direction is interpreted as a horizon, and the number of horizons is large.

[0076] The isochronal interpretation horizon slice refers to: each interpreted horizon is closed and tracked throughout the region according to seismic reflections, and a single interpreted horizon slice represents a slice of a certain sedimentary period.

[0077] The following combines a case to illustrate the method of this embodiment. The area to be predicted is the channel sand body of the first member of the Jurassic Shaximiao Formation in central Sichuan Basin. The specific process is as follows:

[0078] First, determine the impedance type of the sand body, and then determine the reflection characteristics of the target layer sand body through well seismic calibration, such as Figure 2 As shown in the figure, the impedance difference of the sand body in the first section of Shaximiao is smaller than that of the surrounding rock, showing medium-high impedance characteristics. The conventional seismic profile and the synthetic seismic trace do not match. The pseudo-S-wave reflectivity profile result is highly correlated with the synthetic seismic trace, and the sand body is a "peak and valley bright spot" reflection. Specifically, the forward seismic trace uses the P-wave time difference curve, density curve and wavelet as input, obtains the reflection coefficient and calculates it by convolution with the wavelet.

[0079] Then, the AVO attribute inversion is performed using high-quality pre-stack angle stack gathers as input, and the pseudo-S-wave reflectivity profile is obtained based on the inversion results, such as Figure 3 and Figure 4 As shown in Figure 2, for medium and high impedance sand bodies, the “peak and valley bright spot” characteristics of sand body reflection on the pseudo-S-wave reflectivity profile are more obvious than those on conventional seismic profiles. Specifically, AVO attribute inversion is achieved through the Aki-Richards equation.

[0080] Then, the root mean square amplitude of the PG pseudo-S-wave reflectivity attribute and the original seismic data is calculated respectively, and then the obtained root mean square amplitude is normalized and added and fused to obtain a fused attribute body. After the fusion, the low impedance and medium and high impedance on the attribute profile show the characteristics of "high value bright spots" compared with the surrounding rock.

[0081] Finally, for the plane identification of sand bodies, the first choice is to track the entire target layer based on global automatic volume tracking technology, on this basis, high-density isochronal slices are obtained, and the fused seismic attributes are extracted using high-density isochronal slices to characterize the sand body distribution. Figure 5 This is the fused seismic attribute extracted from a certain isochronous slice of the first section of the Shaximiao Formation. Figure 7 The root mean square amplitude of pseudo-shear wave reflectivity can better highlight the distribution of low-impedance sand bodies. Figure 6 The original seismic RMS amplitude can better highlight the distribution of medium and high impedance sand bodies, and has the advantages of two attributes at the same time, realizing the mixed impedance sand body characterization on the same attribute body.

[0082] The above is only a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art shall not deviate from the spirit and scope of the present invention, and shall be within the scope of protection of the claims attached to the present invention.

Claims

1. A method for identifying hybrid impedance sand bodies based on pre-stack pseudo-shear wave reflectivity attributes, characterized in that Including: Determine the impedance type of the sand body; Based on the impedance type of the sand body, determine the seismic response characteristics of the sand body through well-seismic calibration; Based on the seismic response characteristics of the sand body, apply pre-stack seismic angle gather data for AVO attribute inversion to obtain the P-G pseudo-shear wave reflectivity attribute; Calculate the root-mean-square amplitude of the P-G pseudo-shear wave reflectivity attribute and the original seismic data respectively, and perform amplitude normalization on the root-mean-square amplitude of the P-G pseudo-shear wave reflectivity attribute and the root-mean-square amplitude of the original seismic data; Perform amplitude addition calculation on the root-mean-square amplitude of the amplitude-normalized P-G pseudo-shear wave reflectivity attribute and the root-mean-square amplitude of the original seismic data to obtain a fused attribute volume; Adopt a high-density isochronal slice extraction method based on global automatic volume tracking to obtain the amplitude values of the fused attribute volume, and depict the planar distribution of the sand body according to the amplitude values of the fused attribute volume; The well-seismic calibration is the process of obtaining the simulated seismic trace through wavelet and seismic reflection coefficient convolution. The mathematical form of the seismic convolution model is: X(t) = W(t) * R(t) + N(t) In the formula, X(t) represents the seismic record; W(t) is the seismic wavelet; R(t) is the formation reflection coefficient; N(t) is the random environmental noise; The extraction method of the high-density isochronal slice is as follows: Establish a relative isochronal framework model based on global automatic volume tracking; Based on the relative isochronal framework model, extract high-density isochronal interpretation horizon slices according to the top and bottom windows of the target layer required to obtain high-density isochronal slices; The method for obtaining the P-G pseudo-shear wave reflectivity attribute is as follows: Based on the pre-stack seismic angle gather data, apply the Aki-Richards equation to obtain the AVO attribute; Obtain the intercept and gradient according to the AVO attribute, and perform interpolation on the intercept and gradient to obtain the P-G pseudo-shear wave reflectivity attribute; The method for obtaining the root-mean-square amplitude of the original seismic data is as follows: Within a given time window, calculate the average value of the sum of the squares of the amplitudes of the original seismic data; Take the square root of the average value of the sum of the squares of the amplitudes of the original seismic data to obtain the root-mean-square amplitude of the original seismic data.

2. The method for identifying hybrid impedance sand bodies based on pre-stack pseudo-shear wave reflectivity attributes according to claim 1, wherein The method for obtaining the root-mean-square amplitude of the P-G pseudo-shear wave reflectivity attribute is as follows: Within a given time window, calculate the average value of the sum of the squares of the amplitudes of the P-G pseudo-shear wave reflectivity attribute; Take the square root of the average value of the sum of the squares of the amplitudes of the P-G pseudo-shear wave reflectivity attribute to obtain the root-mean-square amplitude of the P-G pseudo-shear wave reflectivity attribute.

3. The hybrid impedance sand body identification method based on pre-stack pseudo-S-wave reflectivity attributes according to claim 1, wherein The amplitude normalization of the root-mean-square amplitude of the P-G pseudo-shear wave reflectivity attribute and the root-mean-square amplitude of the original seismic data includes: Respectively regularize the value ranges of the root-mean-square amplitude of the P-G pseudo-shear wave reflectivity attribute and the root-mean-square amplitude of the original seismic data into the same value range space [1 - 10000] through mathematical algorithms.

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