Optimized ANFIS Model Using Aquila Optimizer for Oil Production Forecasting

AlRassas, Ayman Mutahar; Al-qaness, Mohammed A. A.; Ewees, Ahmed A.; Ren, Shaoran; Elaziz, Mohamed Abd; Damaševičius, Robertas; Krilavičius, Tomas

doi:10.3390/pr9071194

Cited by 95 publications

(39 citation statements)

References 48 publications

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“…Tight sandstone can be defined as a potential reservoir with permeability less than 1 mD or 0.1 × 10 −3 µm 2 and porosity less than 12% [1]. As per contemporary reports of 2019, hydrocarbon shares more than 58% of the world's energy consumption [2]. To suffice the energy needs, tight sandstone gas is presently the leading unconventional natural gas source globally and has developed into a vital parameter for natural gas production [3].…”

Section: Introductionmentioning

confidence: 99%

Sedimentary Facies Controls for Reservoir Quality Prediction of Lower Shihezi Member-1 of the Hangjinqi Area, Ordos Basin

et al. 2022

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The tight gas reserves in the Hangjinqi area are estimated at 700 × 109 m3. Since the exploration of the Hangjinqi, numerous wells are already drilled. However, the Hangjinqi remains an exploration area and has yet to become a gas field. Identifying a paleo-depositional framework such as braided channels is beneficial for exploration and production companies. Further, braided channels pose drilling risks and must be properly identified prior to drilling. Henceforth, based on the significance of paleochannels, this study is focused on addressing the depositional framework and sedimentary facies of the first member (P2x1) of the lower Shihezi formation (LSF) for reservoir quality prediction. Geological modeling, seismic attributes, and petrophysical modeling using cores, logs, interval velocities, and 3D seismic data are employed. Geological modeling is conducted through structural maps, thickness map, and sand-ratio map, which show that the northeastern region is uplifted compared to northwestern and southern regions. The sand-ratio map showed that sand is accumulated in most of the regions within member-1. Interval velocities are incorporated to calibrate the acoustic impedance differences of mudstone and sandstone lithologies, suggesting that amplitude reflection is reliable and amplitude-dependent seismic attributes can be employed. The Root Mean Square (RMS) attribute confirmed the presence of thick-bedded braided channels. The results of cores and logging also confirmed the presence of braided channels and channel-bars. The test results of wells J34 and J72 shows that the reservoir quality within member-1 of LSF is favorable for gas production within the Hangjinqi area.

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Section: Introductionmentioning

confidence: 99%

Sedimentary Facies Controls for Reservoir Quality Prediction of Lower Shihezi Member-1 of the Hangjinqi Area, Ordos Basin

et al. 2022

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“…We discuss other notable examples from the literature below. Alrassas [37] proposed a modified ANFIS (adaptive neuro-fuzzy inference system) model created using the Aquila Optimizer (AO), a novel optimization technique. The AO is a recently developed optimization algorithm influenced by the natural behavior of Aquila.…”

Section: Related Workmentioning

confidence: 99%

Agent State Flipping Based Hybridization of Heuristic Optimization Algorithms: A Case of Bat Algorithm and Krill Herd Hybrid Algorithm

Damaševičius

Maskeliūnas

2021

Algorithms

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This paper describes a unique meta-heuristic technique for hybridizing bio-inspired heuristic algorithms. The technique is based on altering the state of agents using a logistic probability function that is dependent on an agent’s fitness rank. An evaluation using two bio-inspired algorithms (bat algorithm (BA) and krill herd (KH)) and 12 optimization problems (cross-in-tray, rotated hyper-ellipsoid (RHE), sphere, sum of squares, sum of different powers, McCormick, Zakharov, Rosenbrock, De Jong No. 5, Easom, Branin, and Styblinski–Tang) is presented. Furthermore, an experimental evaluation of the proposed scheme using the industrial three-bar truss design problem is presented. The experimental results demonstrate that the hybrid scheme outperformed the baseline algorithms (mean rank for the hybrid BA-KH algorithm is 1.279 vs. 1.958 for KH and 2.763 for BA).

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“…Especially, the AO has been proposed for such a short time that few scholars have improved this algorithm. Currently, because of its strong exploration capability and robustness, the AO has been modified by a few scholars to apply it to problems such as oil production forecasting [24], population forecast [25], task scheduling [26], and so on. For the moment, it has not been applied to the path planning of autonomous intelligent unmanned systems.…”

Section: Introductionmentioning

confidence: 99%

IHSSAO: An Improved Hybrid Salp Swarm Algorithm and Aquila Optimizer for UAV Path Planning in Complex Terrain

et al. 2022

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In this paper, we propose a modified hybrid Salp Swarm Algorithm (SSA) and Aquila Optimizer (AO) named IHSSAO for UAV path planning in complex terrain. The primary logic of the proposed IHSSAO is to enhance the performance of AO by introducing the leader mechanism of SSA, tent chaotic map, and pinhole imaging opposition-based learning strategy. Firstly, the tent chaotic map is utilized to substitute the randomly generated initial population in the original algorithm to increase the diversity of the initial individuals. Secondly, we integrate the leader mechanism of SSA into the position update formulation of the basic AO, which enables the search individuals to fully utilize the optimal solution information and enhances the global search capability of AO. Thirdly, we introduce the pinhole imaging opposition-based learning in the proposed IHSSAO to enhance the capability to escape from the local optimization. To verify the effectiveness of the proposed IHSSAO algorithm, we tested it against SSA, AO, and five other advanced meta-heuristic algorithms on 23 classical benchmark functions and 17 IEEE CEC2017 test functions. The experimental results indicate that the proposed IHSSAO is superior to the other seven algorithms in most cases. Eventually, we applied the IHSSAO, SSA, and AO to solve the UAV path planning problem. The experimental results verify that the IHSSAO is superior to the basic SSA and AO for solving the UAV path planning problem in complex terrain.

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Optimized ANFIS Model Using Aquila Optimizer for Oil Production Forecasting

Cited by 95 publications

References 48 publications

Sedimentary Facies Controls for Reservoir Quality Prediction of Lower Shihezi Member-1 of the Hangjinqi Area, Ordos Basin

Sedimentary Facies Controls for Reservoir Quality Prediction of Lower Shihezi Member-1 of the Hangjinqi Area, Ordos Basin

Agent State Flipping Based Hybridization of Heuristic Optimization Algorithms: A Case of Bat Algorithm and Krill Herd Hybrid Algorithm

IHSSAO: An Improved Hybrid Salp Swarm Algorithm and Aquila Optimizer for UAV Path Planning in Complex Terrain

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