Abstract Background: In shale basins, petroleum systems are complex; they hold data sources in Big Data scales. The motivation of research lies with the facts exploring effective inherent connectivity between unconventional systems. energy reservoir is ambiguous within a distinctive ecosystem. Heterogeneity and multidimensionality unstructured additional challenges, precluding systematic modell...

This paper presents a comparative study of the performance of three versions of Adaptive Neuro-Fuzzy Inference System (ANFIS) hybrid model and two innovative hybrid models in the prediction of oil and gas reservoir properties. ANFIS is a hybrid learning algorithm that combines the rule-based inferencing of fuzzy logic and the back-propagation learning procedure of Artificial Neural Networks. Fu...

This paper discusses the implementation of a numerical method for simulating petroleum reservoirs, based on finite volume technique using non-structured grids, designed for parallel computing platforms with distributed-memory, particularly for clusters of workstations. Non-structured meshes are used in order to enhance the capability of conforming the irregular boundary of the reservoir allowin...

This paper discusses the use of large field-scale reservoir simulation to model multiphase fluid flow processes that occur in giant oil reservoirs. The goal of large-scale studies is to model fluid flow with sufficient details to account for reservoir heterogeneity, various reservoir-wellbore configurations, and complex fluid-rock interactions. In this paper, we developed a black-oil reservoir ...

Biosurfactant producers are crucial for incremental oil production in microbial enhanced oil recovery (MEOR) processes. The isolation of biosurfactant-producing bacteria from oil reservoirs is important because they are considered suitable for the extreme conditions of the reservoir. In this work, a novel biosurfactant-producing strain Acinetobacter junii BD was isolated from a reservoir to red...

The use of Artificial Neural Network (ANN) especially Backpropagation Neural Network (BPNN) has been a promising tool for well log analysis in predicting permeability. However, due to the range of permeability data, it is normally converted using logarithmic transform before being used for data analysis by the BPNN. This has an impact on the accuracy of the permeability prediction. This paper s...

The idea of injecting low salinity water into a petroleum reservoir is not novel and was often used in the 70’s prior to the injection of surfactant. Yet, recently it was shown that simply injecting sufficiently low salinity water improves oil recovery (LoSalTM). Many possible mechanisms concerning Low salinity waterflood have been proposed in the literature. This paper describes an experimenta...

Tidal sandstone reservoirs contain significant intervals of hydrocarbonbearing heterolithic facies, characterized by the presence of tidegenerated sedimentary structures such as flaser, wavy, and lenticular bedding (millimeter to centimeter sand-mud alternations). We have characterized the reservoir properties (sandstone connectivity, effective permeability, and displacement efficiency) of thes...