Nonlinear amplitude inversion using a hybrid quantum genetic algorithm and the exact zoeppritz equation

Cheng, Jiwei; Zhang, Feng; Li, Xiang‐Yang

doi:10.1016/j.petsci.2021.12.014

Cited by 11 publications

(4 citation statements)

References 43 publications

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“…This is due to the fact that more often the models that suit the data will be chosen for replication. The model's fitness value determines the selection probability 12 . The crossover genetic operator is applied after the models have been chosen and coupled.…”

Section: Methodology Genetic Algorithmmentioning

confidence: 99%

Qualitative and quantitative reservoir characterization using seismic inversion based on particle swarm optimization and genetic algorithm: A comparative case study

Kant

Maurya

Singh

2023

Preprint

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Accurate reservoir characterization is necessary to effectively monitor, manage, and increase production. A seismic inversion methodology using a genetic algorithm (GA) and particle swarm optimization (PSO) technique has been devised in thisstudy to characterize the reservoir both qualitatively and quantitatively. It has always been difficult and expensive to disclose deeper reservoirs in exploratory operations when using traditional approaches for reservoir characterization hence inversion based on advanced technique (based on GA and PSO) is proposed in this study. The main goal is to use GA and PSO to significantly lower the fitness (error) function between real seismic data and modeled synthetic data, which will allow us to estimate subsurface properties and, ultimately, accurately characterize the reservoir. Using two synthetic data and one real data from the Blackfoot field in Canada, the study examined subsurface acoustic impedance and porosity in the inter-well zone. Porosity and acoustic impedance are layer features, but seismic data is an interface property, hence these characteristics provide more useful and applicable reservoir information. The inverted results aid in the understanding of seismic data by providing incredibly high-resolution images of the subsurface. Both the GA and the PSO algorithms deliver outstanding results for both simulated and real data. The inverted section accurately anticipated a high porosity zone (> 20%) that supported thehigh seismic amplitude anomaly by having a low acoustic impedance (6000-8500m/s∗ g/cc). This unusual zone is categorized as a reservoir (sand channel) and is located in the 1040–1065 ms time range. In this inversion process, after 400 iterations, thefitness error falls from 1 to 0.88 using GA optimization, compared to 1 to 0.25 using PSO. The convergence time for GA is 670680 seconds, but the convergence time for PSO optimization is 356400 seconds, showing that the former requires 88% more time than the latter. The study recommends PSO application over GA in any E & P project because PSO inversion delivers faster convergence times, excellent error minimization, and high-resolution subsurface data compared to inversion utilizing GA optimization.

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Section: Methodology Genetic Algorithmmentioning

confidence: 99%

Qualitative and quantitative reservoir characterization using seismic inversion based on particle swarm optimization and genetic algorithm: A comparative case study

Kant

Maurya

Singh

2023

Preprint

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“…Quantum coherence makes quantum computing have strong parallel processing ability. In recent years, the quantum genetic algorithm has contributed to valuable research achievements in solving nonlinear equations [21][22][23]. In this paper, the quantum genetic algorithm is introduced into the form-finding calculation of the main cable on the space irregular cable plane, and the corresponding fitness function is proposed.…”

Section: Modified Quantum Genetic Algorithmmentioning

confidence: 99%

A New Method for Finding the Shape of the Main Cable in the Special Cable Plane

et al. 2022

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The main cable and suspender of the spatial special-shaped suspension bridge are in the state of spatial stress; the structural stress is more complex than that of the parallel cable plane and finding the shape of the main cable of the spatial special-shaped cable plane is more difficult. In order to solve the problem of finding the shape of the main cable of the special-shaped suspension bridge, a new calculation model and algorithm of the main cable are proposed in this paper. The new calculation model adds constraints on the transverse bridge direction coordinates of the midspan on the basis of the original calculation model. The new calculation model can timely correct the calculation errors in all directions of the control node during the main cable shape finding process and improve the calculation accuracy. The new algorithm is a hybrid algorithm. The algorithm first uses the modified quantum genetic algorithm to solve and calculate the cable end force close to the real value, and then uses the cable end force obtained by the modified quantum genetic algorithm as the initial value to iterate through the modified least squares method. In this paper, a single cable plane curved suspension bridge is taken as the research background, and the differences of different calculation models in the shape-finding calculation of the main cable of the spatial special-shaped cable plane are compared. The results show that the proposed model is more stable in the calculation process, and the proposed algorithm has high accuracy and strong adaptability.

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“…The use of the accurate Zoeppritz equation can not only avoid the introduction of cumulative deviation by approximate equation but also directly and conveniently invert elastic parameters, improving the inversion effect (Zhou et al, 2017;Zhi et al, 2018). For this reason, many scholars have carried out research on the pre-stack inversion of the accurate Zoeppritz equation (Pan et al, 2017;Cheng et al, 2021). (Chen et al, 2022) derived a nonlinear PP-wave reflection coefficient equation in terms of the reflectivity of Young's modulus, Poisson's ratio, and density based on the exact Zoeppritz equation to improve the accuracy of the inversion results.…”

Section: Introductionmentioning

confidence: 99%

Direct pre-stack inversion of elastic modulus using the exact Zoeppritz equation and the application in shale reservoir

Song

Ding

et al. 2023

Front. Earth Sci.

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Young’s modulus and Poisson’s ratio are important for reservoir characterization and rock brittleness prediction in unconventional resource exploration and development. Conventional methods can estimate Young’s modulus and Poisson’s ratio by indirect calculations and direct inversion using approximate expressions, which have cumulative errors and limited accuracy of the estimated results, especially at large incident angles. In this study, we derived a new form of the Zoeppritz equation and P-to-P wave reflection coefficient in terms of density and Young’s modulus, Poisson’s ratio. It has the same accuracy as the original Zoeppritz equation over a wide range of incident angles. A robust non-linear inversion method based on the iteratively regularized Levenberg Marquardt (IRLM) algorithm, is used to invert all three parameters based on the new equation directly and simultaneously. Synthetic data and field data are used to test and verify the proposed direct inversion method, ensuring the feasibility and effectiveness of the proposed method and the high accuracy and stability of the inversion results. This study has a great potential and valuable guidance for “sweet spot” evaluation and subsequent horizontal well deployment and hydraulic fracturing.

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Nonlinear amplitude inversion using a hybrid quantum genetic algorithm and the exact zoeppritz equation

Cited by 11 publications

References 43 publications

Qualitative and quantitative reservoir characterization using seismic inversion based on particle swarm optimization and genetic algorithm: A comparative case study

Qualitative and quantitative reservoir characterization using seismic inversion based on particle swarm optimization and genetic algorithm: A comparative case study

A New Method for Finding the Shape of the Main Cable in the Special Cable Plane

Direct pre-stack inversion of elastic modulus using the exact Zoeppritz equation and the application in shale reservoir

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