Metaheuristic optimization approaches to predict shear-wave velocity from conventional well logs in sandstone and carbonate case studies

Niri, Mohammad Emami; Kolajoobi, Rasool Amiri; Arbat, Mohammad Khodaiy; Raz, Mahdi Shahbazi

doi:10.1088/1742-2140/aaaba2

Cited by 10 publications

(4 citation statements)

References 35 publications

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“…Metaheuristic algorithms are optimization algorithms designed to find good enough solutions in in limited computational time by evaluating potential solutions and performing strategies and operations to refine them (Niri et al, 2018;Waqas et al, 2023). These methods, excel in addressing highly non-linear optimization problems and thus supply a promising approach for applications in oil and gas exploration (Abdullahi Mu'azu, 2023;Yan et al, 2020).…”

Section: Metaheuristic and Simulated Annealing (Sa) Methodmentioning

confidence: 99%

“…Local search metaheuristics (like simulated annealing) endeavor to discover a suitable solution by iteratively involving slight modifications on a single (current) solution. Constructive metaheuristics (like ant colony optimization attempt to build up solutions from their constituent pieces rather than improving entire solutions (Abdullahi Mu'azu, 2023;Niri et al, 2018;Norbakhsh Razmi et al, 2023;Vasile et al, 2022;Yan et al, 2021). Simulated annealing can assemble to the global minimum, and because of so many perturbations during the optimization process, the starting point has a negligible effect on the final answer (Mahmoodpour and Masihi, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Estimating elastic properties of sediments by pseudo-wells generation utilizing simulated annealing optimization method

Khah,

Salehi,

Kianoush

et al. 2024

Preprint

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The hydrate concentration model considerably affects elastic properties, including bulk and shear modulus. Defining seismic properties of sediments, such as compressional and shear wave velocity and density, provides valuable information to identify rock facies and fluid types. This information commonly results from pre-stack seismic inversion, while post-stack seismic information provides acoustic impedance as a layer-based property. Traditionally, seismic inversion requires well logs to produce an initial guess of inversion routines and provide a low-frequency part of the amplitude spectrum. Eventually, seismic inversion methods could not be performed in the areas without well-log data, such as deep sea areas. In such cases, pseudo-well logs derived from pre-stack seismic data are a solution. Pseudo-well generation is a title used to estimate the elastic parameters of sediments in areas, such as deep marine environments, where drilled wells are absent or sparse. Metaheuristic optimization algorithms are suitable tools for minimizing the cost function as they best match real and synthetic seismic data. In this study, the SEAM earth model has been used as a reference to investigate the quality of pseudo-well generation utilizing a simulated annealing (SA) algorithm as an optimization method of property model change, which minimizes the cost function of seismic inversion. As a result, considering an initial model type of the SEAM model, simultaneous seismic inversion introduced the best compressional and shear wave velocities and density logs, which provide the best real and synthetic seismic data match when synthetic data is calculated from the simplified Zoeppritz equation.

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Section: Metaheuristic and Simulated Annealing (Sa) Methodmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimating elastic properties of sediments by pseudo-wells generation utilizing simulated annealing optimization method

Khah,

Salehi,

Kianoush

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Metaheuristic algorithms are optimization algorithms designed to find good enough solutions in a small amount of computing time by evaluating potential solutions and performing strategies and operations on them (Niri et al, 2018;Waqas et al, 2023). Metaheuristic search techniques, e.g., bioinspired optimization algorithms such as genetic algorithms, can handle highly non-linear optimization concerns and thus supply a promising approach for oil and gas exploration (Abdullahi Mu'azu, 2023;Yan et al, 2020).…”

Section: Metaheuristic and Simulated Annealing (Sa) Methodmentioning

confidence: 99%

“…Local search metaheuristics (such as simulated annealing attempt to find a good solution by iteratively applying small changes on a single (current) solution. Constructive metaheuristics (such as ant colony optimization try to build up solutions from their constituent parts instead of enhancing complete solutions (Abdullahi Mu'azu, 2023;Niri et al, 2018;Vasile et al, 2022;Yan et al, 2021). Although Evolutionary algorithms (EAs), swarm intelligence (SI), and intelligent optimization algorithms have become widely utilized for geophysical inversion and can obtain satisfactory results, they still involve certain limitations in solving the nonlinear inversion of geophysics, such as premature convergence and lower convergence in the later period.…”

Section: Introductionmentioning

confidence: 99%

Estimation of elastic properties of sediments utilizing simulated annealing algorithm – a pseudo-wells generation approach

Khah,

Salehi,

Kianoush

et al. 2023

Preprint

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The gas hydrate distribution model containing cement, or un-cement models, considerably affects elastic properties such as shear and bulk modulus. Thus, determining the distribution model in the hydrate-bearing sediments requires decreasing uncertainty in quantitative studies based on seismic velocities. Pre-stack seismic data include additional fluid information than post-stack seismic data, and the pre-stack inversion procedure has influential benefits such as stable outcomes, high resolution, and strong manageability. The amplitude-variation-with-angle (AVA) inversion along the bottom simulating reflector (BSR) utilizing compressional and Shear wave pre-stack analysis could be involved to evaluate hydrate and gas saturations at the pseudo well, especially in accretionary prism structures. It could change unconsolidated sediments' elastic properties and produce sharp bottom simulating. Pseudo-well generation is a title for estimating the elastic parameters of sediments in areas such as deep marine environments where drilled wells are absent (or sparse). This seismic angle-gather inversion problem has complex space and several local and global optimum solutions. In such cases, metaheuristic algorithms are a suitable tool for problem-solving. In this paper, the metaheuristic Simulated Annealing algorithm has been investigated, and the developed optimized algorithm has been presented. In order to analyze the performance of the algorithm, pre-stack seismic data is utilized as a benchmark. The conceptual model of this data includes the elastic parameter logs, which makes it an appropriate option for analyzing the performance and accuracy of the algorithm. According to the results, the generation of pseudo-wells with the algorithm mentioned earlier can be used to characterize hydrates-bearing sediments.

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An adding‐points strategy surrogate model for well control optimization based on radial basis function neural network

Chen,

Xu,

et al. 2024

Can J Chem Eng

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This work introduces a new adding points strategy for augmenting the accuracy of reservoir proxy model and improving the effect of well control optimization. The method is based on the optimization process of a radial basis function neural network and genetic algorithm (GA), which aids in identifying the more important points to be included in the sample space. Notably, the uniqueness of this method lies in selecting the points of higher importance for subsequent optimization processes across the entire sample space. These selected points are then added to the surrogate model. The surrogate model is updated for each generation until the termination condition is satisfied, enabling the surrogate model to achieve improved accuracy. The results show that the new method is more effective, superior, and converges faster than the traditional method.

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Metaheuristic optimization approaches to predict shear-wave velocity from conventional well logs in sandstone and carbonate case studies

Cited by 10 publications

References 35 publications

Estimating elastic properties of sediments by pseudo-wells generation utilizing simulated annealing optimization method

Estimating elastic properties of sediments by pseudo-wells generation utilizing simulated annealing optimization method

Estimation of elastic properties of sediments utilizing simulated annealing algorithm – a pseudo-wells generation approach

An adding‐points strategy surrogate model for well control optimization based on radial basis function neural network

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