Total Organic Carbon Predictions from Lower Barnett Shale Well-log Data Applying an Optimized Data Matching Algorithm at Various Sampling Densities
Sign Up to like & getrecommendations! Published in 2020 at "Pure and Applied Geophysics"
DOI: 10.1007/s00024-020-02566-1
Abstract: Accurately estimating total organic carbon (TOC) from suites of well logs is essential as it is too costly and time consuming to take direct measurements from core samples in many wells. Unfortunately, the several methods… read more here.
Keywords: data matching; sampling densities; well log; lower barnett ... See more keywords
Geothermal potential of the St. Lawrence Lowlands sedimentary basin from well log analysis
Sign Up to like & getrecommendations! Published in 2018 at "Geothermics"
DOI: 10.1016/j.geothermics.2018.04.004
Abstract: Abstract The heterogeneous distribution of minerals in different rock types poses several challenges for assessing thermal conductivity, heat flow and temperature of sedimentary basins, especially when databases coming from the oil sector are the only… read more here.
Keywords: methodology; temperature; well log; thermal conductivity ... See more keywords
Brittleness index predictions from Lower Barnett Shale well-log data applying an optimized data matching algorithm at various sampling densities
Sign Up to like & getrecommendations! Published in 2020 at "Geoscience frontiers"
DOI: 10.1016/j.gsf.2020.09.016
Abstract: Abstract The capability of accurately predicting mineralogical brittleness index (BI) from basic suites of well logs is desirable as it provides a useful indicator of the fracability of tight formations. Measuring mineralogical components in rocks… read more here.
Keywords: brittleness index; data matching; index; matching algorithm ... See more keywords
Lithological facies classification using deep convolutional neural network
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Petroleum Science and Engineering"
DOI: 10.1016/j.petrol.2018.11.023
Abstract: Abstract The aim of this paper is the development of an effective model based on deep learning for geological facies classification in wells. Facies classification is carried out by studying the lithological properties of rocks,… read more here.
Keywords: facies classification; model; neural network; well log ... See more keywords
Evaluation of consolidation parameter data trendings and comparison between prediction models for well-log velocities: A case study from the Namorado Oilfield (southern Brazil)
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Petroleum Science and Engineering"
DOI: 10.1016/j.petrol.2019.04.036
Abstract: Abstract The compressional and shear-wave velocities ( V P and V S ) have been used in studies for hydrocarbon exploration over the last decades. Nevertheless, the absence of S-wave velocity records in geophysical surveys… read more here.
Keywords: evaluation consolidation; namorado oilfield; well log; consolidation parameter ... See more keywords
Application of nanoindentation for uncertainty assessment of elastic properties in mudrocks from micro- to well-log scales
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DOI: 10.1190/geo2016-0545.1
Abstract: Uncertainty in estimates of elastic properties of soft mudrock components such as clay minerals and kerogen can influence well-log-based evaluation of effective elastic properties in organic-rich mudrocks. Existing methods, such as effective medium models for… read more here.
Keywords: uncertainty; application nanoindentation; well log; log based ... See more keywords
Integration of seismic and well-log data using statistical and neural network methods
Sign Up to like & getrecommendations! Published in 2017 at "Geophysics"
DOI: 10.1190/tle36040324.1
Abstract: In the last two to three decades, the use of seismic attributes for reservoir characterization and modeling has grown exponentially. Now, a dozen or more attributes are often extracted from seismic data to predict reservoir… read more here.
Keywords: data using; integration; log data; well log ... See more keywords
Automated Well-Log Processing and Lithology Classification by Identifying Optimal Features Through Unsupervised and Supervised Machine-Learning Algorithms
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DOI: 10.2118/202477-pa
Abstract: The application of specialized machine learning (ML) in petroleum engineering and geoscience is increasingly gaining attention in the development of rapid and efficient methods as a substitute to existing methods. Existing ML-based studies that use… read more here.
Keywords: well log; lithology; machine learning; well logs ... See more keywords