Facies classification with different machine learning algorithm – An efficient artificial intelligence technique for improved classificationPartha Pratim MandalReza Rezaee
For complex machine learning tasks like facies classification, feature engineering is often critical. This paper shows the inclusion of physics-motivated feature interaction in feature augmentation can further improve the capability of machine learning in rock facies classification. We demonstrate this ...
Classification of coastal sedimentary environments Sedimentary Geology (1992) M.E. Brookfield The evolution of the great river systems of southern Asia during the Cenozoic India–Asia collision: rivers draining southwards Geomorphology (1998) L.A. Buatois et al. Sequence stratigraphic and sedimentologic...
Seismic facies analysis which is aimed at identifying subsurface geological features from seismic data, has evolved due to the time-consuming and labor-intensive nature of its traditional approach. To address these challenges, numerical frameworks such as machine learning have been applied, yet attribute...
Mohri M, Rostamizadeh A, Talwalkar A (2012) Foundations of machine learning. The MIT Press, Cambridge MATH Google Scholar Mollajan A, Mehrgini B, Memarian H (2013) Zonal classification by pattern recognition methods: an example from Asmari formation (Manouri oil field, south of Iran). J...
Electrofacies classification of deeply buried carbonate strata using machine learning methods: A case study on ordovician paleokarst reservoirs in Tarim BasinPaleokarst reservoirsElectrofaciesPCAK-meansLDAThe paleokarst system is one of the main carbonate reservoirs, which can form important super-large ...
In this new ML algorithm, we only need a simple CNN design and structure to efficiently achieve accurate classification of rock facies. We test the feasibility of applying this new algorithm using a verifiable well logging dataset from the Panoma gas field in southwest Kansas. The results show ...
Machine learning methods including support‐vector‐machine and deep learning are applied to facies classification problems using elastic impedances acquired from a Paleocene oil discovery in the UK Central North Sea. Both of the supervised learning approaches showed similar accuracy when predicting facies...
Using deep-learning to predict Dunham textures and depositional facies of carbonate rocks from thin sections Petrographic analysis of thin sections is one of the most important and routinely used methods in a wide range of energy, earth and environmental science a... X Liu,V Chandra,AI Ramdani ...
Deep learningConvolutional neural networkThe aim of this paper is the development of an effective model based on deep learning for geological fades classification in wells. Fades classification is carried out by studying the lithological properties of rocks, which are characteristic of modern sediments,...