Optimized ANFIS Model Using Aquila Optimizer for Oil Production Forecasting

Abstract

Oil production forecasting is one of the essential processes for organizations and governments to make necessary economic plans. This paper proposes a novel hybrid intelligence time series model to forecast oil production from two different oil fields in China and Yemen. This model is a modified ANFIS (Adaptive Neuro-Fuzzy Inference System), which is developed by applying a new optimization algorithm called the Aquila Optimizer (AO). The AO is a recently proposed optimization algorithm that was inspired by the behavior of Aquila in nature. The developed model, called AO-ANFIS, was evaluated using real-world datasets provided by local partners. In addition, extensive comparisons to the traditional ANFIS model and several modified ANFIS models using different optimization algorithms. Numeric results and statistics have confirmed the superiority of the AO-ANFIS over traditional ANFIS and several modified models. Additionally, the results reveal that AO is significantly improved ANFIS prediction accuracy. Thus, AO-ANFIS can be considered as an efficient time series tool.

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

“…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].…”

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

“…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.…”

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

“…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.…”