CN119439276A - Wave equation forward modeling-based correction method for amplitude of seismic waves reflected by inclined interface - Google Patents
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Abstract
The invention relates to a wave equation forward modeling-based inclination interface reflection seismic wave amplitude correction method, belonging to the technical field of reservoir prediction of oil and gas field exploration, which comprises the steps of firstly establishing geological models with 3 different inclination angle characteristics based on three-dimensional post-stack seismic data of a research area, well logging data of a well completion, a target layer and seismic horizon data above the target layer, then adopting a wave equation forward modeling method to perform seismic forward modeling, and extracting the amplitude and dip angle data of the target layer reflected seismic wave on the forward record, adopting a least square fitting method to obtain a quadratic fitting function of the amplitude and dip angle, adopting the quadratic fitting function of the amplitude and dip angle obtained by forward simulation analysis to calculate a simulated reflected seismic wave amplitude array of the target layer, and correcting the real reflected wave amplitude array of the target layer to obtain an amplitude array of the target layer which can be effectively used for reservoir prediction.
Description
Technical Field
The invention relates to the technical field of oil and gas field exploration, in particular to a wave equation forward modeling-based inclined interface seismic event amplitude correction method.
Background
In the seismic exploration in the field of oil and gas field exploration, a reservoir is a main target to be searched, for the reservoir which grows near the top, the response characteristic of the reservoir is that the amplitude of an earthquake phase axis is weakened at the development part of the reservoir due to the existence of a top strong reflection interface, the amplitude of the earthquake phase axis of the top interface can qualitatively indicate the development condition of the top reservoir under the condition of small level or stratum inclination, and the conventional amplitude correction method (wavelet decomposition reconstruction and the like) highlights the earthquake response characteristic of the reservoir which grows near the top by removing the influence of the earthquake strong reflection of the top interface under the condition of not considering stratum inclination.
However, in the inclined stratum, besides the influence caused by the difference of the impedance of the upper wave and the lower wave of the interface, the influence of the inclination degree of the stratum on the amplitude of the reflection phase axis is also required to be considered, the amplitude of the reflection phase axis caused by the inclined interface is weakened, the amplitude of the reflection phase axis is often far greater than the influence of the reservoir on the reflection phase axis, and at the moment, the accuracy rate of predicting the reservoir by adopting the conventional top interface reflection amplitude attribute is lower. At present, reservoir prediction is carried out through reflection amplitude of a top interface, and the method for removing strong reflection of the top interface earthquake on a reflection interface with smaller horizontal or inclination angles is mainly concentrated at home and abroad, wherein a wavelet decomposition reconstruction method based on matching pursuit is a mainstream method with better effect at present, recently, domestic scholars propose a wavelet decomposition reconstruction technology based on a strong reflection model, and a better application effect is obtained when the distance between the reservoir and the strong reflection interface is smaller than 1/4 wavelength of wavelet.
1. Wavelet decomposition reconstruction technology based on matching pursuit
The method is based on a multi-wavelet seismic channel model, and the seismic channel is decomposed into sets of wavelets with different main frequencies and different amplitudes through decomposition of the seismic wavelets, so that the corresponding relation between the reflection coefficients of different stratum and the seismic wavelets is obtained. All or part of wavelets with different main frequencies and different amplitudes obtained by wavelet decomposition are selected to be overlapped again through the reconstruction of the seismic wavelets to form a new seismic channel, and the effective signals with weaker energy in the seismic reflection are enhanced. The wavelet decomposition and reconstruction based on the matching pursuit algorithm projects the original signal onto a series of orthogonal atoms, the seismic signal is represented by the linear combination of different atoms, and the correction of the shielding effect of the strong reflection interface on the underlying stratum is achieved by analyzing, screening and reconstructing the different atoms.
2. Wavelet decomposition reconstruction technology based on strong reflection model
Based on the strong reflection model, domestic students cross-correlate the seismic records and superimpose the seismic records along the direction of the seismic source, and after the superimposed results are convolved with the original data, superimpose the seismic records along the direction of the detector to obtain the reconstructed first arrival wave. Compared with the original signal, the strong reflection first-arrival signal and the weak reflection first-arrival signal are distinguished, the amplitude spectrum of the weak reflection signal is enhanced, the reconstructed first-arrival signal is subjected to sparse representation, and a base matrix is constructed for solving. After sparse decomposition of the signals is carried out on the seismic signals around the strong reflection, the purpose of removing the strong reflection can be achieved by only cutting off components with larger amplitude in a dynamic dictionary around the strong reflection.
3. Defects of the prior art
1. Wavelet decomposition reconstruction based on a matching pursuit algorithm is mainly based on a multi-wavelet seismic channel model, and under the condition that reflection coefficients and seismic wavelets are unknown, the time length of the matching pursuit algorithm needs longer, and the calculated amount is larger. Based on the matching pursuit algorithm, the atoms are assumed to be mutually orthogonal, and the reservoirs growing at the top of the inclined interface are influenced by the interference of the seismic reflection waves because the range of the reservoirs from the top interface is changed in the longitudinal direction and the transverse direction, so that the orthogonality of the atoms cannot be ensured, and the atoms which are directly decomposed by the matching pursuit method on the original data body generate errors. Amplitude longitudinal and transverse changes caused by interface inclination, and the correlation of amplitude components of atoms nearby the same interface is reduced by a matching pursuit algorithm, so that the calculation accuracy is reduced.
2. When the transversal change of the dip angle of the stratum interface is large, the reliability of the result in the calculation time window is reduced, the error of the reconstructed first arrival wave is increased, and the amplitude of the same phase axis of the inclined interface in the calculation time window is not uniformly distributed, so that the larger component of the amplitude of the signal cut after sparse decomposition can cause larger error.
Therefore, the invention aims at the phenomenon of seismic wave amplitude variation of an inclined interface, namely the phenomenon that the amplitude variation of a phase axis of seismic reflection is uneven along the same wave impedance interface and is greatly influenced by the inclination degree, and discloses an inclined interface reflection seismic wave amplitude correction method based on wave equation forward modeling, wherein a correction function of a target layer interface inclination angle array to a reflection seismic wave amplitude array is established in a certain area.
Disclosure of Invention
The invention relates to an amplitude correction method of a reflection seismic wave of an inclined interface based on wave equation forward modeling, belonging to the technical field of reservoir prediction of oil and gas field exploration. The method comprises the steps of firstly establishing geological models with 3 different dip angle characteristics based on three-dimensional post-stack seismic data of a research area, well logging data of a well completion, a target layer and seismic horizon data above the target layer, then adopting an elastic wave equation post-stack forward modeling method to conduct seismic forward modeling, extracting amplitude and dip angle data of a target layer reflected seismic wave on forward modeling records, adopting least square fitting to obtain a quadratic fit function of the amplitude and the dip angle, extracting an amplitude array and a stratum dip angle array of a target layer interface of the three-dimensional post-stack seismic data along the seismic horizon of the target layer, and adopting the quadratic fit function of the amplitude and the dip angle obtained by forward modeling analysis to calculate a simulated reflected seismic wave amplitude array of the target layer to correct the real reflected wave amplitude array of the target layer, so as to obtain the amplitude array of the target layer which can be effectively used for reservoir prediction.
The method comprises the following specific steps:
(1) Inputting three-dimensional post-stack seismic data of a research area, a target layer and a seismic horizon of a stratum above the target layer, calculating stratum dip angles of a target layer interface, selecting 3 seismic sections of target layers with different dip angles, wherein the target layer dip angles are characterized by large dip angles, medium dip angles and small dip angles, and establishing corresponding 3 stratum grid models based on the target layer and the seismic horizons of the stratum above the target layer;
(2) Inputting well logging data of a well completion of a target layer drilled in a research area, statistically analyzing the layer speed and density of the target layer and a stratum above the target layer, and filling the target layer and the stratum speed and density into 3 stratum grid models in the step 1 to obtain 3 geological models for forward modeling;
(3) Performing forward modeling on the 3 geologic models in the step 2 by adopting a wave equation numerical simulation method to obtain corresponding 3 simulated seismic records, and extracting an amplitude array of reflected seismic waves of the target layer of the 3 simulated records along the seismic horizon of the target layer;
(4) Based on the inclination angle of the target layer in the step 1 and the amplitude array in the step 3, a quadratic fitting function of the amplitude and the inclination angle is obtained by adopting a least square fitting method;
(5) Extracting an amplitude array and a stratum dip angle array of a target layer interface of the three-dimensional post-stack seismic data in the step 1 along the seismic horizon of the target layer, and normalizing the amplitude array to obtain a true reflected seismic wave amplitude array of the target layer;
(6) Based on the inclination angle array in the step 5 and the fitting function of the amplitude-inclination angle in the step 4, calculating an amplitude array corresponding to the inclination angle array in the step 5, and carrying out normalization processing, namely a simulated reflected seismic wave amplitude array of the target layer;
(7) Correcting the real reflection seismic wave amplitude array of the destination layer in the step 5 by adopting the simulated reflection seismic wave amplitude array of the destination layer in the step 6, wherein the corrected reflection seismic wave amplitude array of the destination layer = the real reflection seismic wave amplitude array of the destination layer + 1.0-the simulated reflection seismic wave amplitude array of the destination layer;
(8) And outputting the corrected reflection seismic wave amplitude array of the target layer in the step 7 for reservoir prediction based on the amplitude variation characteristics.
A wave equation forward modeling-based inclined interface seismic event amplitude correction method has the following characteristics that:
(1) In the field of post-stack reservoir prediction, the true response characteristics of formation lithology combination are highlighted by correcting the influence of the formation dip angle on the phase axis amplitude of the reflected wave. And establishing a relation between the stratum dip angle array and the target layer interface reflected wave amplitude array through a wave equation forward result of the geological model, correcting the original interface reflected wave amplitude array through calculating the forward reflected wave amplitude array of the actual target layer interface dip angle, so that the amplitude correction of the seismic reflection interface is achieved, and the method has stronger innovation.
(2) The core of the invention is the necessity of formation dip correction, i.e., whether the corrected results accurately indicate the response characteristics (e.g., amplitude, etc.) of the developing reservoir near the top interface. Through the research of a large number of documents, the superposition and offset processing of the pre-stack CMP gathers cannot well superpose the reflected wave energy of the inclined interfaces, so that the impedance interfaces with the same reflection coefficient in post-stack seismic data have differences in amplitude intensity of the same phase axis on the post-stack seismic section due to different inclination degrees. The amplitude attribute of the common top interface of the reservoir close to the top development indicates the development condition of the top reservoir, and the response characteristic of the top reservoir is weakened under the condition that the inclined interface is not subjected to amplitude correction due to superposition and offset of pre-stack CMP trace gather processing, so that the actual impedance difference above and below the interface cannot be accurately reflected by extracting the conventional amplitude attribute. According to the invention, a forward geological model is constructed according to the actual three-dimensional post-stack seismic data, the seismic horizon data and the logging data, and the influence of the dip angle on the interface reflection amplitude is analyzed by controlling the change of the single factor of the dip angle of the stratum, so that a proper correction function is established, and the method has good theoretical basis and feasibility.
Drawings
FIG. 1 is a technical flow chart of the present invention;
FIG. 2 is a seismic section view taken in assisting in the construction of a geologic model;
FIG. 3 is a diagram that assists in illustrating a forward geologic model constructed based on seismic profiles, seismic horizons, and well log data;
FIG. 4 is a post-stack seismic section taken in a wave equation forward simulation for a forward geologic model with assistance in explanation;
FIG. 5 is a plan view of post-stack reservoir predictions before correction of an uncorrected top interface reflection amplitude array;
FIG. 6 is a plan view of post-stack reservoir prediction after dip amplitude correction for the top interface reflection amplitude array.
Detailed Description
Example 1
A wave equation forward modeling-based correction method for the amplitude of a seismic wave reflected by an inclined interface comprises the following steps:
Step 1, inputting a three-dimensional post-stack seismic data volume SA (x, y, t) of a research area, inputting a seismic horizon HT (x, y) of a target layer of the research area and a seismic horizon HT 1(x,y)、HT2(x,y)、…、HTnc (x, y) of a stratum covered by the target layer, wherein nc is the total number of stratum above the target layer of the research area and is determined by the stratum structure of the research area;
step 2, calculating an x-direction visual inclination angle array Px (x, y, t) and a y-direction visual inclination angle array Py (x, y, t) of the three-dimensional data body SA (x, y, t) by using instantaneous frequencies and x, y-direction instantaneous wave numbers in a plurality of analyses, wherein the calculating method adopts a method disclosed in a paper of Zeng Xianghao and the like (2023) in the application of three-dimensional multi-scale body curvature in deep granite buried hill reservoir crack identification, and calculates an inclination angle array P (x, y, t),
Step 3, extracting an inclination angle array HP (x, y) of a target layer in an inclination angle array P (x, y, t) by adopting a target layer seismic horizon array HT (x, y), dividing the inclination angle of the target layer into three scales of large, medium and small according to an HP (x, y) value distribution interval, selecting sections Sx1 (x, y, t), sx2 (x, y, t) and Sx3 (x, y, t) of the target layer in 3 y directions with obvious inclination angle characteristics of the target layer in a three-dimensional post-stack seismic data body, and establishing 3 stratum grid models M1 (x, t), M2 (x, t) and M3 (x, t) corresponding to the sections Sx1 (x, y, t), sx2 (x, y, t) and Sx3 (x, t) based on the target layer of a research area and the stratum horizon arrays above the target layer;
Step 4, inputting well logging data of a well completion of a target layer drilled through a research area, adopting an average analysis method to statistically analyze the layer speeds and densities of the target layer and a stratum above the target layer, and filling the well logging data into the grid model of the stratum in the step 3 to obtain 3 speed models M1_vel (x, t), M2_vel (x, t), M3_vel (x, t) and density models M1_den (x, t), M2_den (x, t) and M3_den (x, t) for forward modeling;
Step 5, based on the velocity model and the density model, obtaining simulation records of 3 models, namely M1_s (x, t), M2_s (x, t) and M3_s (x, t), wherein the calculation method adopts a method disclosed in a paper of 'fine interpretation technology of seismic construction based on wave equation numerical simulation' by Xiong Xiaojun and the like 2011, and adopts a destination layer seismic horizon array HT (x, y) and an inclination angle array P (x, y, t) of step 2 to extract an amplitude array M1_amp (x, t), an M2_amp (x, t), an inclination angle array M1_dip (x), an M2_dip (x) and an M3_dip (x) of a destination layer in the simulation records of 3 models;
Step 6, based on the amplitude array and the dip array of the destination layer in step 5, M1_amp (x, t), M2_amp (x, t), M3_amp (x, t) and M1_dip (x), M2_dip (x), M3_dip (x), fitting the amplitude and the dip by using a least square method, and obtaining fitting coefficients a, b and c in formula 2 by using a method disclosed in the article "least square curve fitting and optimization algorithm research" by Gao Qiuying et al 2021,
amp(θ)=a×θ2+b×θ+c (2)
Step 7, extracting an amplitude array HAmp (x, y) and an inclination array HDmp (x, y) of the target layer by using the target layer seismic horizon array HT (x, y), the inclination array P (x, y, t) of step 2 and the three-dimensional post-stack seismic data volume SA (x, y, t) of the research area of step 1, and obtaining an amplitude array HAmp _S (x, y) by using a fitting relation in a formula 2,
HAmp_S(x,y)=a×HDmp2(x,y)+b×HDmp(x,y)+c (3)
Step 8, normalize the sets HAmp (x, y) and HAmp _S (x, y),
HAmp′(x,y)=HAmp(x,y)÷max(HAmp(x,y)) (4)
HAmp_S′(x,y)=HAmp_S(x,y)÷max(HAmp_S(x,y)) (5)
Wherein HAmp ′ (x, y) and HAmp _s ′ (x, y) are normalized arrays, and max () is a calculated maximum function;
Step 9, correcting HAmp ′ (x, y) by adopting HAmp _S ′ (x, y) array of step 8,
HAmp_E(x,y)=HAmp′(x,y)+1.0-HAmp_S′(x,y) (6)
Wherein HAmp _E (x, y) is a reflected seismic wave amplitude array of the target layer after formation dip correction,
And 10, outputting the corrected reflection seismic wave amplitude array of the target layer in the step 9 for reservoir prediction based on the amplitude variation characteristics.
Example 2
Fig. 5 and 6 are respectively plan views of a post-stack reservoir prediction of a target interval of a research area, in which fig. 5 is a plan view of a reservoir prediction of a reflection amplitude array extracted from three-dimensional seismic data of the research area along a target interval, the coincidence rate of the result and the development condition of a well-completed reservoir is only 67%, and fig. 6 is a plan view of a reservoir prediction of a reflection amplitude array of a target interval, which is obtained by performing dip correction according to the present invention, the coincidence rate of the result and the development condition of a well-completed reservoir is 92%, and it can be seen that the effect of predicting a reservoir by adopting the present invention is better.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (1)
1. The wave equation forward modeling-based inclined interface reflection seismic wave amplitude correction method comprises the following specific steps of:
Step 1, inputting a three-dimensional post-stack seismic data volume SA (x, y, t) of a research area, inputting a seismic horizon HT (x, y) of a target layer of the research area and a seismic horizon HT 1(x,y)、HT2(x,y)、…、HTnc (x, y) of a stratum covered by the target layer, wherein nc is the total number of stratum above the target layer of the research area and is determined by the stratum structure of the research area;
Step 2, calculating an x-direction visual inclination array Px (x, y, t) and a y-direction visual inclination array Py (x, y, t) of the three-dimensional data body SA (x, y, t) by using instantaneous frequencies and x, y-direction instantaneous wave numbers in a plurality of analyses, wherein the calculating method adopts a method disclosed in the article of 'application of three-dimensional multi-scale body curvature in deep granite buried hill reservoir crack identification' of 2023 of Zeng Xianghao and the like, and calculates an inclination array P (x, y, t),
Step 3, extracting an inclination angle array HP (x, y) of a target layer in an inclination angle array P (x, y, t) by adopting a target layer seismic horizon array HT (x, y), dividing the inclination angle of the target layer into three scales of large, medium and small according to an HP (x, y) value distribution interval, selecting sections Sx1 (x, y, t), sx2 (x, y, t) and Sx3 (x, y, t) of the target layer in 3 y directions with obvious inclination angle characteristics of the target layer in a three-dimensional post-stack seismic data body, and establishing 3 stratum grid models M1 (x, t), M2 (x, t) and M3 (x, t) corresponding to the sections Sx1 (x, y, t), sx2 (x, y, t) and Sx3 (x, t) based on the target layer of a research area and the stratum horizon arrays above the target layer;
Step 4, inputting well logging data of a well completion of a target layer drilled through a research area, adopting an average analysis method to statistically analyze the layer speeds and densities of the target layer and a stratum above the target layer, and filling the well logging data into the grid model of the stratum in the step 3 to obtain 3 speed models M1_vel (x, t), M2_vel (x, t), M3_vel (x, t) and density models M1_den (x, t), M2_den (x, t) and M3_den (x, t) for forward modeling;
Step 5, based on the velocity model and the density model, obtaining simulation records of 3 models, namely M1_s (x, t), M2_s (x, t) and M3_s (x, t), wherein the calculation method adopts a method disclosed in a paper of 'fine interpretation technology of seismic construction based on wave equation numerical simulation' by Xiong Xiaojun and the like 2011, and adopts a destination layer seismic horizon array HT (x, y) and an inclination angle array P (x, y, t) of step 2 to extract an amplitude array M1_amp (x, t), an M2_amp (x, t), an inclination angle array M1_dip (x), an M2_dip (x) and an M3_dip (x) of a destination layer in the simulation records of 3 models;
Step 6, based on the amplitude array and the dip array of the destination layer in step 5, M1_amp (x, t), M2_amp (x, t), M3_amp (x, t) and M1_dip (x), M2_dip (x), M3_dip (x), fitting the amplitude and the dip by using a least square method, and obtaining fitting coefficients a, b and c in formula 2 by using a method disclosed in the article "least square curve fitting and optimization algorithm research" by Gao Qiuying et al 2021,
amp(θ)=a×θ2+b×θ+c (2)
Step 7, extracting an amplitude array HAmp (x, y) and an inclination array HDmp (x, y) of the target layer by using the target layer seismic horizon array HT (x, y), the inclination array P (x, y, t) of step 2 and the three-dimensional post-stack seismic data volume SA (x, y, t) of the investigation region of step 1, and using an amplitude array HAmp _S (x, y) of the fitting coefficient in formula 2,
HAmp_S(x,y)=a×HDmp2(x,y)+b×HDmp(x,y)+c (3)
Step 8, normalize the sets HAmp (x, y) and HAmp _S (x, y),
HAmp′(x,y)=HAmp(x,y)÷max(HAmp(x,y)) (4)
HAmp_S′(x,y)=HAmp_S(x,y)÷max(HAmp_S(x,y)) (5)
Wherein HAmp ′ (x, y) and HAmp _s ′ (x, y) are normalized arrays, and max () is a calculated maximum function;
Step 9, correcting HAmp ′ (x, y) by adopting HAmp _S ′ (x, y) array of step 8,
HAmp_E(x,y)=HAmp′(x,y)+1.0-HAmp_S′(x,y) (6)
Wherein HAmp _E (x, y) is a reflected seismic wave amplitude array of the target layer after formation dip correction;
And 10, outputting the corrected reflection seismic wave amplitude array of the target layer in the step 9 for reservoir prediction based on the amplitude variation characteristics.
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