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  1.  33
    A Comparison of Classification Techniques for Seismic Facies Recognition.Tao Zhao, Vikram Jayaram, Atish Roy & Kurt J. Marfurt - 2015 - Interpretation: SEG 3 (4):SAE29-SAE58.
    During the past decade, the size of 3D seismic data volumes and the number of seismic attributes have increased to the extent that it is difficult, if not impossible, for interpreters to examine every seismic line and time slice. To address this problem, several seismic facies classification algorithms including [Formula: see text]-means, self-organizing maps, generative topographic mapping, support vector machines, Gaussian mixture models, and artificial neural networks have been successfully used to extract features of geologic interest from multiple volumes. Although (...)
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  2.  18
    Introduction to Special Section: Pattern Recognition and Machine Learning.Vikram Jayaram, Per Age Avseth, Kostia Azbel, Theirry Coléou, Deepak Devegowda, Paul de Groot, Dengliang Gao, Kurt Marfurt, Marcilio Matos, Tapan Mukerji, Manuel Poupon, Atish Roy, Brian Russell, Brad Wallet & Vikas Kumar - 2015 - Interpretation: SEG 3 (4):SAEi-SAEii.
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  3.  8
    A New Method for Fracture Toughness Determination of Graded Al Bond Coats by Microbeam Bend Tests.Nagamani Jaya B., Vikram Jayaram & Sanjay Kumar Biswas - 2012 - Philosophical Magazine 92 (25-27):3326-3345.
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  4. Quantifying the Sensitivity of Seismic Facies Classification to Seismic Attribute Selection: An Explainable Machine-Learning Study.David Lubo-Robles, Deepak Devegowda, Vikram Jayaram, Heather Bedle, Kurt J. Marfurt & Matthew J. Pranter - 2022 - Interpretation 10 (3):SE41-SE69.
    During the past two decades, geoscientists have used machine learning to produce a more quantitative reservoir characterization and discover hidden patterns in their data. However, as the complexity of these models increases, the sensitivity of their results to the choice of the input data becomes more challenging. Measuring how the model uses the input data to perform either a classification or regression task provides an understanding of the data-to-geology relationships which indicates how confident we are in the prediction. To provide (...)
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  5. Introduction to Special Section: Permian Basin Challenges and Opportunities.Sumit Verma, Olga Nedorub, Fangyu Li, Tao Zhao, Mohamed Zobaa, Robert Trentham, Ron Bianco & Vikram Jayaram - 2019 - Interpretation 7 (4):SKi-SKi.
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  6.  5
    Introduction to Special Section: Machine Learning in Seismic Data Analysis.Haibin Di, Tao Zhao, Vikram Jayaram, Xinming Wu, Lei Huang, Ghassan AlRegib, Jun Cao, Mauricio Araya-Polo, Satinder Chopra, Saleh Al-Dossary, Fangyu Li, Erwan Gloaguen, Youzuo Lin, Anne Solberg & Hongliu Zeng - 2019 - Interpretation 7 (3):SEi-SEii.
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  7.  5
    Machine Learning Regressors and Their Metrics to Predict Synthetic Sonic and Mechanical Properties.Ishank Gupta, Deepak Devegowda, Vikram Jayaram, Chandra Rai & Carl Sondergeld - 2019 - Interpretation 7 (3):SF41-SF55.
    Planning and optimizing completion design for hydraulic fracturing require a quantifiable understanding of the spatial distribution of the brittleness of the rock and other geomechanical properties. Eventually, the goal is to maximize the stimulated reservoir volume with minimal cost overhead. The compressional and shear velocities can also be used to calculate Young’s modulus, Poisson’s ratio, and other mechanical properties. In the field, sonic logs are not commonly acquired and operators often resort to regression to predict synthetic sonic logs. We have (...)
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  8.  5
    Optimization of Clamped Beam Geometry for Fracture Toughness Testing of Micron-Scale Samples.B. Nagamani Jaya, Sanjit Bhowmick, S. A. Syed Asif, Oden L. Warren & Vikram Jayaram - 2015 - Philosophical Magazine 95 (16-18):1945-1966.
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  9.  3
    Introduction to Special Section: Cloud Computing.Bradley Wallet, Konstantin Osypov, Victor Aarre, Sumit Verma, Oswaldo Davogustto, Bo Zhang, Vikram Jayaram & Shuang Zhang - 2021 - Interpretation 9 (1):SAi-SAi.
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  10.  1
    Introduction to Special Section: Insights to Digital Oilfield Data Using Artificial Intelligence and Big Data Analytics.Vikram Jayaram, Atish Roy, Bill Barna, Deepak Devegowda, Jacqueline Floyd, Pradeepkumar Ashok, Aria Abubakar, Anisha Kaul & Emmanuel Schnetzler - 2019 - Interpretation 7 (3):SFi-SFi.
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