阅读说明：本技术 一种模型约束的薄层多波ava联合反演方法 (Thin-layer multi-wave AVA joint inversion method based on model constraint ) 是由 杨春 王赟 孙鹏远 张铁强 于 2019-10-25 设计创作，主要内容包括：本发明涉及一种模型约束的薄层多波AVA联合反演方法,包括：根据薄层模型m,计算薄层频变反射系数R<Sub>PP</Sub>(f)、R<Sub>PS</Sub>(f)；求取频率域地震子波W<Sub>PP</Sub>(f)、W<Sub>PS</Sub>(f)；计算频率域的薄层AVA道集S<Sub>PP</Sub>(f)、S<Sub>PS</Sub>(f)；计算时间域的薄层AVA道集s<Sub>PP</Sub>(t)、s<Sub>PS</Sub>(t),并带入建立的薄层AVA联合反演的目标函数Q(m)；判断Q(m)是否小于误差阀值或者迭代次数是否大于最大迭代次数；若否,利用LM算法,计算模型更新量Δm,并重新计算薄层频变反射系数R<Sub>PP</Sub>(f)、R<Sub>PS</Sub>(f),进行迭代计算,直至精度或者迭代次数满足要求。若是,输出反演结果m,薄层模型参数m包含薄层三层介质的纵波速度、横波速度、密度及薄层厚度。本发明充分地利用了薄层多波信息,相比常规地震反演方法,可以获得更为准确的薄层弹性参数及厚度反演结果。(The invention relates to a thin-layer multi-wave AVA joint inversion method based on model constraint, which comprises the following steps: calculating the thin layer frequency-dependent reflection coefficient R according to the thin layer model m PP (f)、R PS (f) (ii) a Solving frequency domain seismic wavelets W PP (f)、W PS (f) (ii) a Thin-layer AVA gather S for computing frequency domain PP (f)、S PS (f) (ii) a Thin-layer AVA gather s for computing time domain PP (t)、s PS (t) and introducing the target function Q (m) of the built thin-layer AVA joint inversion; judging whether Q (m) is smaller than an error threshold value or whether the iteration number is larger than the maximum iteration number; if not, calculating the model updating quantity delta m by utilizing an LM algorithm, and recalculating the thin-layer frequency-dependent reflection coefficient R PP (f)、R PS (f) And carrying out iterative calculation until the precision or the iteration times meet the requirements. If yes, outputting an inversion result m, wherein the thin layer model parameters m comprise the longitudinal wave velocity, the transverse wave velocity, the density and the thin layer thickness of the thin layer three-layer medium. The invention fully utilizes the thin-layer multi-wave information, and can obtain more accurate thin-layer elastic parameters and thickness inversion results compared with the conventional seismic inversion method.)

1. A thin-layer multiwave AVA joint inversion method based on model constraint is characterized by comprising the following steps:

s1, inputting the thin layer model m, and calculating the thin layer frequency-dependent reflection coefficient R by using the thin layer accurate reflection coefficient equation_PP(f)、R_PS(f)；

S2, obtaining the seismic wavelet w of the time domain according to the actual seismic record_PP(t)、w_PS(t)；

S3, according to w_PP(t)、w_PS(t) using FFT to obtain frequency domain seismic wavelet W_PP(f)、W_PS(f)；

S4, calculating a thin-layer AVA gather S of the frequency domain_PP(f)、S_PS(f)，S_PP(f)＝R_PP(f)·W_PP(f)、S_PS(f)＝R_PS(f)·W_PS(f)；

S5, calculating a thin-layer AVA trace set S of a time domain by using FFT inverse transformation_PP(t)、s_PS(t)；

S6, establishing an objective function Q (m) of thin-layer AVA joint inversion, and converting S_PP(t)、s_PS(t) substituting the objective function q (m);

s7, judging whether Q (m) is smaller than an error threshold value or whether the iteration times are larger than the maximum iteration times;

s8, if Q (m) is larger than or equal to the error threshold value and the iteration times are smaller than or equal to the maximum iteration times, calculating the model update amount delta m by utilizing an LM algorithm;

s9, updating the model parameter m to m + delta m, returning the updated thin layer model m to S1, and performing iterative computation until the precision meets the requirement or the iteration number is larger than the maximum iteration number;

and S10, if Q (m) is less than the error threshold value, or the iteration times are more than the maximum iteration times, outputting an inversion result m, wherein the thin layer model parameters m comprise the longitudinal wave velocity, the transverse wave velocity, the density and the thin layer thickness of the thin layer three-layer medium.

2. The model-constrained thin-layer multi-wave AVA joint inversion method of claim 1, wherein the thin-layer model parameters m comprise longitudinal wave velocity, transverse wave velocity, density and thin-layer thickness of a thin-layer three-layer medium.

3. The model-constrained thin-layer multiwave AVA joint inversion method of claim 1, wherein in step S6, the objective function q (m) ═ η | | d_PP-s_PP||²+(1-η)||d_PS-s_PS||²Wherein eta is the weight of the PP wave, and 1-eta is the weight of the PS wave.

4. The model-constrained thin-layer multiwave AVA joint inversion method of claim 1, wherein in step S8, the model update quantity Δ m is calculated by using an LM algorithm, and satisfies the following formula:

Δm＝[H(m)+λI]^-1J^T(m)[s(m₀+Δm)-d(m₀)]；

wherein H (m) is Hessian matrix, and has H (m) ═ J^T(m) J (m), λ is damping coefficient, I is unit matrix, s is fitting seismic AVA trace set, and represents s_PPOr s_PSD is the actual AVA gather, representing d_PPOr d_PSJ is the Jacobian matrix and has:

5. the model-constrained thin-layer multi-wave AVA joint inversion method of claim 1, wherein in step S3, the frequency domain seismic wavelets W are obtained_PP(f)、W_PS(f) The following formula is satisfied:

W_PP(f)＝FFT[w_PP(t)]；

W_PS(f)＝FFT[w_PS(t)]。

6. the model-constrained thin-layer multi-wave AVA joint inversion method of claim 1, characterized in thatIn step S5, the thin layer AVA gather S of the computation time domain_PP(t)、s_PS(t) satisfies the following formula:

s_PP(t)＝FFT^-1[S_PP(f)]；

s_PS(t)＝FFT^-1[S_PS(f)]。

Technical Field

The invention relates to the technical field of seismic exploration, in particular to a thin-layer multi-wave AVA joint inversion method based on model constraint.

Background

With the continuous and deep development of resources such as oil gas, coal and the like in China, complex oil and gas reservoirs such as lithologic reservoirs, carbonate fracture-cave reservoirs, unconventional oil gas and the like and coal reservoirs become the key points of exploration. In east regions or some western basins of China, most of middle and new continental facies oil-containing basins are mainly deposited by thin-layer sand and mudstone, and a small amount of carbonate rock, shale and paste salt layers are clamped, the lithology and the thickness of the strata are greatly changed in the transverse direction, and the thickness of the strata is far lower than the vertical resolution of the current seismic technology and exists in the form of the thin layers. The thickness of coal beds of coal series strata in China is mostly between 2 and 10m, and often the coal beds of coal series strata and sand-shale exist in a thin interbed mode, and the reflection response is not generated by a single interface, but is a composite wave formed by superposing top-bottom reflection, interbed multiples and converted waves. Seismic techniques based on single impedance difference interfaces, thick layer reflections, are increasingly challenging and subject to unacceptable errors. Therefore, the inversion method research based on the thin layer reflection theory is carried out, and the method has important practical significance for development of seismic exploration of oil gas, coal and the like.

Disclosure of Invention

The present invention aims to solve the above-mentioned disadvantages of the prior art.

In order to achieve the above object, an embodiment of the present invention provides a thin-layer multiwave AVA joint inversion method based on model constraints, including the following steps: s1, inputting the thin layer model m, and calculating the thin layer frequency-dependent reflection coefficient R by using the thin layer accurate reflection coefficient equation_PP(f)、R_PS(f) In that respect S2, obtaining the seismic wavelet w of the time domain according to the actual seismic record_PP(t)、w_PS(t) of (d). S3, according to w_PP(t)、w_PS(t) using FFT to obtain frequency domain seismic wavelet W_PP(f)、W_PS(f) In that respect S4, calculating a thin-layer AVA gather S of the frequency domain_PP(f)、S_PS(f)，S_PP(f)＝R_PP(f)·W_PP(f)、S_PS(f)＝R_PS(f)·W_PS(f) In that respect S5, calculating a thin-layer AVA trace set S of a time domain by using FFT inverse transformation_PP(t)、s_PS(t) of (d). S6, establishing an objective function Q (m) of thin-layer AVA joint inversion, and converting S_PP(t)、s_PS(t) into the objective function Q (m). S7, judging whether Q (m) is smaller than the error threshold or whether the iteration number is larger than the maximum iteration number. And S8, if Q (m) is larger than or equal to the error threshold value and the iteration times are smaller than or equal to the maximum iteration times, calculating the model updating amount Δ m by using an LM algorithm. And S9, updating the model parameter m to m + delta m, returning the updated thin layer model m to S1, and performing iterative computation until the precision meets the requirement or the iteration number is greater than the maximum iteration number. And S10, if Q (m) is less than the error threshold value, or the iteration times are more than the maximum iteration times, outputting an inversion result m, wherein the thin layer model parameters m comprise the longitudinal wave velocity, the transverse wave velocity, the density and the thin layer thickness of the thin layer three-layer medium.

In one possible embodiment, the thin layer model parameters m include the longitudinal wave velocity, the transverse wave velocity, the density and the thin layer thickness of the thin layer three-layer medium.

In one possible embodiment, in step S6, the target function q (m) ═ η | | | d_PP-s_PP||²+(1-η)||d_PS-s_PS||²Wherein eta is the weight of the PP wave, and 1-eta is the weight of the PS wave.

In one possible embodiment, in step S8, the model update amount Δ m is calculated using the LM algorithm, and satisfies the following equation:

Δm＝[H(m)+λI]^-1J^T(m)[s(m₀+Δm)-d(m₀)]；

wherein H (m) is Hessian matrix, and has H (m) ═ J^T(m) J (m), λ is damping coefficient, I is unit matrix, s is fitting seismic AVA trace set, and represents s_PPOr s_PSD is the actual AVA gather, representing d_PPOr d_PSJ is the Jacobian matrix and has:

k＝1,2,…，10。

in one possible embodiment, in step S3, a frequency domain seismic wavelet W is derived_PP(f)、W_PS(f) The following formula is satisfied:

W_PP(f)＝FFT[w_PP(t)]；

W_PS(f)＝FFT[w_PS(t)]。

in one possible implementation, in step S5, a thin-layer AVA gather S of the time domain is computed_PP(t)、s_PS(t) satisfies the following formula:

s_PP(t)＝FFT^-1[S_PP(f)]；

s_PS(t)＝FFT^-1[S_PS(f)]。

the invention fully utilizes the thin-layer multi-wave information, and can obtain more accurate thin-layer elastic parameters and thickness inversion results compared with the conventional seismic inversion method.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 is a schematic flow chart of a thin-layer multiwave AVA joint inversion method according to an embodiment of the present invention;

FIG. 2 is a flowchart of a thin-layer multiwave AVA joint inversion method according to an embodiment of the present invention;

FIG. 3 is an AVA gather of model 1 according to an embodiment of the present invention;

FIG. 4 shows the inversion result of model 1 according to an embodiment of the present invention;

FIG. 5 is an AVA gather for model 2 provided by an embodiment of the present invention;

FIG. 6 shows the inversion result of model 2 according to an embodiment of the present invention;

FIG. 7 is an AVA gather of model 3 according to an embodiment of the present invention;

FIG. 8 is an inversion result of model 3 provided by an embodiment of the present invention;

FIG. 9 is an AVA gather for model 4 provided by an embodiment of the present invention;

fig. 10 shows the inversion result of model 4 according to an embodiment of the present invention.

Detailed Description