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1

Identifying the potash reservoirs from seismic data by using convolution neural network, constrained by the waveform characteristics of potash reservoirs

Zhu Lei, Zhang Fanchang, Xu Xunyong, Xu Wanglin

Acta Geophysica

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2023

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Vol. 71, no. 6

2699--2714

EN

Exploration of potash resources under complex geological condition is particularly important. However, it is difficult to establish characteristic equations for direct prediction, since there is no direct relation between potash content (PC) and seismic response. To solve this problem, this paper proposed a potash reservoir prediction method by a specially designed convolution neural network (CNN) structure to train the special waveform and petrophysical characteristics of potash reservoirs. Considering that the potash reservoirs and petrophysical characteristics are not a one-to-one mapping, the prediction procedure is divided into two parts. First, a CNN is constructed for potash reservoir prediction, according to the spatial waveform characteristics of potash reservoirs. The mapping between potash reservoirs and waveform characteristics is used to obtain the potash reservoir probability data by the soft-max function. Then, another CNN for PC prediction is built based on the petrophysical characteristics of potash reservoirs. Meanwhile, according to the Hadamard criterion, the petrophysical characteristics of potash reservoir are constrained by the waveform characteristics. The two CNN models are used to directly predict the PC synergistically. Consequently, the bidirectional mapping problem can be alleviated and a loss function of the PC prediction CNN constrained with the waveform is obtained. Finally, by tuning the PC prediction CNN through the loss function, PC prediction is performed. The correlation between the predicted and true PC values can reach more than 80%.

2

Multi-trace post-stack seismic data sparse inversion with nuclear norm constraint

Dai Ronghuo, Zhang Fanchang, Yin Cheng, Hu Ying

Acta Geophysica

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2021

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Vol. 69, no. 1

53--64

EN

Among many seismic inversion methods, the sparse spike inversion for post-stack seismic data uses the migrated and stacked seismic data which is regarded as zero ofset refection seismic data in the case of normal incidence to extract refectivity and impedance of underground rocks. The seismic refectivity and impedance can refect underground rocks’ lithology, petrophysical property, oil–gas possibility, and so forth. However, the common used post-stack seismic inversion adopts single trace in the process of inversion and completes the whole data cube’s inversion through trace by trace. It cannot use lateral regularization. Hence, the lateral continuity of single trace inversion result is poor. It is difcult to represent the lat eral variation features of underground rocks. Based on the conventional sparse spike inversion, the nuclear norm of matrix in the matrix completion theory is introduced in the process of post-stack seismic inversion. At the same time, the strategy of multi-trace seismic data simultaneous inversion is used to carry out lateral regularization constraint. Numerical tests on 2D model indicate that the inversion results obtained from the proposed method can clearly represent not only the vertical variation features but also the lateral variation features of underground rocks. At last, the inversion results of real seismic data further show the feasibility and superiority of the proposed method in practical application.

3

Frequency‑dependent energy attenuation and velocity dispersion in periodic layered media

Zhang Heng, Zhang Fanchang, Lu Yawei

Acta Geophysica

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2019

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Vol. 67, no. 3

799--811

EN

According to Brajanovski periodic layered model, a fractural medium can be equivalent to layered media with periodic distribution of fractural layers and background layers, but the analytical solution given by Brajanovski can only interpret the dispersion and attenuation effects of single characteristic unit model. In order to study the dispersion and attenuation features of multiple characteristic units, forward modeling methods are needed. Based on the theory of two-phase medium, Biot deduced the propagation equation of longitudinal waves in fluid-saturated porous media. However, there are two problems in the forward modeling using time-domain equation. One is the influences of boundary reflection, and the other is the introduction of cumulative error. For convenience, time-domain equation is rewritten in the frequency domain, thus constructing a one-dimensional rock physics model. Then, forward method is used to study the dispersion and attenuation features of fluid-saturated medium. Numerical simulation results are found to be in good agreement with the analytical solution. Furthermore, the frequency-domain forward method can analyze the velocity dispersion and energy attenuation of longitudinal waves in any multilayered fracture medium. By analyzing those numerical simulation results, it can be obtained that, as the length of characteristic unit increases or the number of characteristic unit decreases, both the starting frequency of dispersion and the peak frequency of attenuation shift to low, whatever the attenuation peaks are equal. In addition, the effects of porosity, permeability and fluid saturation on energy attenuation and velocity dispersion are also studied. Finally, the stress field and displacement field distributions of fluid-saturated fractural medium are given by the frequency-domain forward modeling method.