AIMC Topic: Oil and Gas Fields

Clear Filters Showing 1 to 10 of 10 articles

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

PloS one Jan 7, 2025
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...
Neural Networks, Computer Support Vector Machine Anisotropy Oil and Gas Fields Machine Learning Models, Theoretical
View on PubMed DOI

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 Dec 4, 2024
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...
Oklahoma Deep Learning Water Wells California Oil and Gas Fields Neural Networks, Computer
View on PubMed DOI

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

Anais da Academia Brasileira de Ciencias May 20, 2024
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...
Geologic Sediments Oil and Gas Fields Support Vector Machine Bayes Theorem Machine Learning
View on PubMed DOI

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

Scientific reports Sep 13, 2022
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...
Porosity Natural Gas Geology Neural Networks, Computer Oil and Gas Fields
View on PubMed DOI

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

Computational intelligence and neuroscience Jun 21, 2022
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...
Machine Learning Oil and Gas Fields
View on PubMed DOI

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

PloS one Apr 26, 2021
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...
Oil and Gas Fields Statistics as Topic Sand Time Factors Models, Theoretical Fuzzy Logic Stress, Mechanical
View on PubMed DOI

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

PloS one Nov 10, 2020
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...
Population Density Oil and Gas Fields Fishes California Surveys and Questionnaires Animals Water Ecosystem Robotics Environmental Monitoring Biodiversity
View on PubMed DOI

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

Environmental science and pollution research international May 24, 2018
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...
Fresh Water Humans Air Pollution Nigeria Water Quality Atmosphere Water Pollutants, Chemical Metals Environment Fuzzy Logic Oil and Gas Fields Models, Theoretical Environmental Monitoring
View on PubMed DOI

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

Journal of fish biology Aug 3, 2017
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 ...
Fishes Behavior, Animal Biodiversity Iran Animals Food Chain Robotics Oil and Gas Fields Population Dynamics
View on PubMed DOI

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 Oct 4, 2016
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...
Oil and Gas Fields Models, Theoretical Humans Pressure Neural Networks, Computer
View on PubMed DOI
Popular Topics
Recent Journals