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Prediction of coalbed methane content based on seismic identification of key geological parameters: a case in a study area, Southern Qinshui Basin

Liu Jing, Chang Suoliang, Zhang Sheng, Li Yanrong, Hao Yaju, He Guoxian, He You, Liu Bo

Acta Geophysica

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2023

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Vol. 71, no. 6

2645--2662

EN

The coalbed methane content (CMC) is an important parameter to evaluate the degree of coalbed methane enrichment, and also an important reservoir parameter to calculate coalbed methane resources, productivity prediction and reservoir simulation. Accurately identifying the distribution of CMC is crucial to the exploration of CBM. In this study, we developed a prediction method for the CMC distribution via seismic techniques identification of key geological parameters such as structure, coal thickness and sedimentation. Firstly, the geological factors that control the generation and preservation of CBM in the study area are quantitatively characterized by using five parameters: surface (X1), residual (X2), dip (X3), coal thickness (X4) and the ratio of sand to mud (X5). Secondly, the geological parameters are extracted by seismic structure interpretation and inversion prediction technology. Thirdly, the key geological parameters of CMC are screened out by grey correlation analysis. Finally, the functional relationship of CMC and the key geological parameters is established to predict the CMC distribution. The method is applied to the CMC distribution prediction of two coal seams of a study area in the southern Qinshui Basin, China. Results show that different coal seams differ in key geological parameters of CMC, resulting in various CMC distribution laws. The CMC prediction method based on the key geological factors can effectively delineate the CBM enrichment area in the study area, providing important reference for the CBM exploration and development.

2

Precise time‑depth conversion of coal measure strata based on velocity splicing: a case application in Qinshui basin

Zhang Qifan, Chang Suoliang, Zhang Sheng, Zhao Lipeng, Shi Xiaohong, Guo Chunsheng, Yu Guangming, Liu Jing, Liu Bo

Acta Geophysica

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2023

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Vol. 71, no. 4

1729--1746

EN

Transforming seismic data from the time domain to the depth domain is a very important step when using 3D seismic exploration to guide the exploration and development of coalbed methane (CBM). However, the conventional time-depth conversion method has difficulty meeting the control accuracy requirements of CBM development based on horizontal well technology when the 3D seismic data in a mining area are old. Therefore, a precise time-depth conversion method was found to improving the accuracy of time-depth conversion, which is based on the splicing of seismic inversion velocity and poststack migration velocity. The first step of this method is obtaining the standard layers in the time domain by precise interpretation of seismic data. Then, the inversion velocity and poststack migration velocity are spliced to obtain the complete interval velocity volume of the study area, and the results are corrected. The next step is the prediction of the coal seam floor elevation based on the spliced velocity, and the predicted coal seam floor elevation is corrected by borehole data. Finally, the mesh is between standard layers in the depth domain to obtain the 3D data volume in the depth domain. The method was applied to the time-depth conversion of 3D seismic data in the Yangquan X study area. The results show that the relative error between the predicted results and the borehole data of No. 3, No. 8 and No. 15 coal seam is only 0.72% through the validation of the reserved boreholes, indicating that the method is effective. This study provides a precise method of time-depth conversion for seismic data when there is only poststack seismic data in the mining area, which can not only improve the interpretation accuracy of standard layers but can also improve the prediction accuracy of other layers between standard layers, which can better guide the well location arrangement of coalfield and CBM.

3

Integrated seismic–geological prediction of tectonic coal via main controlling factors

Liu Jing, Chang Suoliang, Zhang Sheng, Li Yanrong, Chen Qiang

Acta Geophysica

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2022

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Vol. 70, no 1

173--190

EN

Tectonic coal in coal seams not only seriously restricts the development of coalbed methane (CBM), but also easily forms coal and gas outburst risk areas. Therefore, it is of great significance to effectively predict the tectonic coal in coal seams under the development scale. Currently, the prediction methods of tectonic coal include geological prediction and geophysical prediction. Due to the large scale of geological analysis and the low identifiability of geophysical response of thin coal seam, these two methods are difficult to meet the prediction requirements of tectonic coal in the development process. Therefore, this paper proposes a new method for predicting tectonic coal based on seismic–geological integrated analysis of main controlling fac tors. Firstly, the control factors of tectonic coal and their quantitative characterization are determined by geological analysis. Then, the characterization parameters of control factors are obtained by various seismic technologies. Finally, the main control factors are screened by grey correlation analysis, and the prediction model of tectonic coal distribution is established by using the main control factors, and applied in the Qinshui Basin. The results show that the structure, surrounding rock lithology and coal thickness are three kinds of geological factors controlling the development of tectonic coal and the control weight of each factor is different. Structure plays the most important role in controlling the development of tectonic coal, followed by coal thickness and surrounding rock lithology. The prediction error of two verification wells is less than 2%, which indicates that the method can provide effective guidance for coal structure evaluation in the process of CBM development and coal mining.

4

Research on hybrid modeling and predictive energy management for power split hybrid electric vehicle

Wang Shaohua, Zhang Sheng, Shi Dehua, Sun Xiaoqiang, Yang Tao

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2021

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Vol. 69, nr 3

art. no. e137064

EN

Due to the coexistence of continuity and discreteness, energy management of a multi-mode power split hybrid electric vehicle (HEV) can be considered a typical hybrid system. Therefore, the hybrid system theory is applied to investigate the optimum energy distribution strategy of a power split multi-mode HEV. In order to obtain a unified description of the continuous/discrete dynamics, including both the steady power distribution process and mode switching behaviors, mixed logical dynamical (MLD) modeling is adopted to build the control-oriented model. Moreover, linear piecewise affine (PWA) technology is applied to deal with nonlinear characteristics in MLD modeling. The MLD model is finally obtained through a high level modeling language, i.e. HYSDEL. Based on the MLD model, hybrid model predictive control (HMPC) strategy is proposed, where a mixed integer quadratic programming (MIQP) problem is constructed for optimum power distribution. Simulation studies under different driving cycles demonstrate that the proposed control strategy can have a superior control effect as compared with the rule-based control strategy.

5

Suppression of multiple refection–refraction waves in the shallow low velocity zone via vertical source combination

Chang Suoliang, Qu Zhen, Zhang Sheng, Fu Yanning, Chen Qiang

Acta Geophysica

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2021

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Vol. 69, no. 5

1799--1811

EN

In seismic data from areas with low-velocity structures, a special type of multiple reflected refraction often appears, which seriously affects the effective refection wave of adjacent target layers and causes distortion of the refection wave shape. Based on the kinematic characteristics of the seismic wave field in shallow low-velocity zones, we demonstrate the generation mechanism of multiple reflected refractions. Then, a method of suppressing multiple reflected refractions through vertically combined dual sources is proposed. First, according to the relative position relationship between multiple reflection refractions and the effective wave, prerequisites for the suppression of multiple reflected refractions are established. Second, the optional range of vertical combination parameters is calculated according to the source combination equation, which is used to adjust the relative position of the two sources set vertically in the low-velocity zone. Subsequently, model data verification and application of the Loess Plateau exploration area prove that the vertical source combination method can suppress multiple reflected refractions in shallow low-velocity zones and effectively improve the signal-to-noise ratio of seismic data.

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Adaptive individual weight-gain AVO inversion with smooth nonconvex regularization

Du Siyuan, Zhang Jiashu, Zhang Sheng, Hu Guangmin

Acta Geophysica

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2021

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Vol. 69, no. 4

1199--1213

EN

Amplitude variation with ofset (AVO) inversion is a widely used approach to obtain reliable estimates of elastic parameter in the felds of seismic exploration. However, the AVO inversion is an ill-posed problem because of the band-limited characteristic of seismic data. The regularization constraint plays an important role in improving inversion resolution. Total variation (TV) class regularization based on L1 norm has been introduced in seismic inversion. But, these methods may underestimate the high-amplitude components and obtain low-resolution results. To tackle these issues, we propose to combine a smooth nonconvex regularization approach with adaptive individual weight-gain. Compared with the L1 norm regularizers, the proposed smoothed nonconvex sparsity-inducing regularizers can lead to more accurate estimation for high-amplitude components. Diferent from previous regularization methods, the proposed approach also assigns diferent weight regularization parameters for diferent strata, which we call adaptive individual weight-gain strategy. To ensure sufcient minimization of the constructed objective function, a spectral Polak–Ribière–Polyak conjugate gradient method with line search step size is used. Further, we prove that the proposed algorithm converges to a stationary point. The synthetic data tests illustrate that our approach has improved performance compared with the conventional TV class regularization methods. Field data example further verifes the higher resolution of the proposed approach.