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Oil and Gas Fields

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Echo State Networks for data-driven downhole pressure estimation in gas-lift oil wells.

Neural networks : the official journal of the International Neural Network Society
Process measurements are of vital importance for monitoring and control of industrial plants. When we consider offshore oil production platforms, wells that require gas-lift technology to yield oil production from low pressure oil reservoirs can beco...

Vertical zonation and functional diversity of fish assemblages revealed by ROV videos at oil platforms in The Gulf.

Journal of fish biology
An assessment of vertical distribution, diel migration, taxonomic and functional diversity of fishes was carried out at offshore platforms in The (Arabian-Iranian-Persian) Gulf. Video footage was recorded at the Al Shaheen oil field between 2007 and ...

Anthropogenic activities impact on atmospheric environmental quality in a gas-flaring community: application of fuzzy logic modelling concept.

Environmental science and pollution research international
We present a modelling concept for evaluating the impacts of anthropogenic activities suspected to be from gas flaring on the quality of the atmosphere using domestic roof-harvested rainwater (DRHRW) as indicator. We analysed seven metals (Cu, Cd, Pb...

A comparison of two remotely operated vehicle (ROV) survey methods used to estimate fish assemblages and densities around a California oil platform.

PloS one
Offshore oil and gas platforms have a finite life of production operations. Once production ceases, decommissioning options for the platform are assessed. The role that a platform's jacket plays as fish habitat can inform the decommissioning decision...

A robust fuzzy logic-based model for predicting the critical total drawdown in sand production in oil and gas wells.

PloS one
Sand management is essential for enhancing the production in oil and gas reservoirs. The critical total drawdown (CTD) is used as a reliable indicator of the onset of sand production; hence, its accurate prediction is very important. There are many p...

Application of Machine Learning to Predict Estimated Ultimate Recovery for Multistage Hydraulically Fractured Wells in Niobrara Shale Formation.

Computational intelligence and neuroscience
The completion design of multistage hydraulic fractured wells including the cluster spacing injected proppant and slurry volumes has shown a great influence on the well production rates and estimated ultimate recovery (EUR). EUR estimation is a criti...

Shale gas geological "sweet spot" parameter prediction method and its application based on convolutional neural network.

Scientific reports
Parameters such as gas content (GAS), porosity (PHI) and total organic carbon (TOC) are key parameters that reveal the shale gas geological "sweet spot" of reservoirs. However, the lack of a three-dimensional high-precision prediction method is not c...

Machine learning-based classification of petrofacies in fine laminated limestones.

Anais da Academia Brasileira de Ciencias
Characterization and development of hydrocarbon reservoirs depends on the classification of lithological patterns from well log data. In thin reservoir units, limited vertical data impedes the efficient classification of lithologies. We present a tes...

A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: A Case Study for California and Oklahoma.

Environmental science & technology
Undocumented Orphaned Wells (UOWs) are wells without an operator that have limited or no documentation with regulatory authorities. An estimated 310,000 to 800,000 UOWs exist in the United States (US), whose locations are largely unknown. These wells...

Seismic anisotropy prediction using ML methods: A case study on an offshore carbonate oilfield.

PloS one
Estimating seismic anisotropy parameters, such as Thomson's parameters, is crucial for investigating fractured and finely layered geological media. However, many inversion methods rely on complex physical models with initial assumptions, leading to n...