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The AAPG/Datapages Combined Publications Database
Showing 1,733 Results. Searched 195,364 documents.
Abstract: Dynamical Systems Theory of Gulf Coast Shelf-Clinoform Stratigraphy, by Michael Simms; #90167 (2013)
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2013
Abstract: Wave Gradiometry Using a Three-dimensional Array of Experimental MEMS- based Accelerometers, by Donny T. Dangkua, Charles A. Langston, and Chris H. Cramer; #90182 (2013)
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2013
Non-Linear Full-Waveform Inversion Using Geological Prior Knowledge
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Carbonate Stratigraphy and Organic Matter Preservation Within the Scotian Margin, Offshore Nova Scotia
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What Difference Does a Eustatic Curve Make?
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Processing and Interpretation Considerations for Full Waveform Inversion of PSDM Velocity Fields
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Three-Dimensional Numerical Modeling of Eustatic Control on Continental-Margin Sand Distribution
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Application of Facies-Constrained Inversion Technology to Prediction of Lacustrine Carbonate Reservoir in Yingxi, Qaidam Basin (Northwest China)
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Surrounding Rock Influence Correction for Array Laterolog Responses with Borehole Eccentricities in Horizontal Wells
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Inference of Organic Carbon Content of Shale From Zoeppritz PP-AVO Inversion: Case Study of Avalon Shale, Delaware Basin
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Coupling Between Sedimentation and Deformation: How Emergence of Mini-Basins Connects to Turbidity-Current Sedimentation
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Experimental Investigation on the Effect of Wettability on Rock-Electricity Response in Sandstone Reservoirs
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Application of Surrogate Models and Derivative-free Optimization in Geothermal Reservoir Modelling
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ABSTRACT: Predicting Log Properties from Seismic Data Using Abductive Networks; #90051 (2006)
Osama A. Ahmed, Radwan Abdel-Aal, Husam AlMustafa
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... predictors from the available set of seismic attributes. 2. Abductive Networks are nonlinear predictors which are proven to outperform linear predictors...
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Abstracts: Empirical Mode Decomposition and Robust Seismic Attribute Analysis; #90173 (2015)
Jiajun Han and Mirko van der Baan
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.... (1998) is a powerful signal analysis technique to detect non-stationary and nonlinear signal systems. Furthermore, high-resolution timefrequency analysis...
2015
Abstracts: A Decomposition of RP into Contributions from single-parameter Reflectivities; #90173 (2015)
Kristopher A. Innanen
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... nonlinear terms provide a significant increase in accuracy over the linear/Aki-Richards approximation in several large contrast/large angle model regimes...
2015
Abstracts: Application of the Signal Correlation for the Construction of Age Models of Lake Baikal Sedimentary Records; #90173 (2015)
Karol Rohraff, Vadim A. Kravchinsky, and Mauricio D. Sacchi
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..., May 9-11, 2011 the method of MacDonald (1989), as it allows the possibility of investigation of irregularly spaced data resulting from a nonlinear...
2015
Abstract: The Shale Activity Test (SAT); #90254 (2016)
Konstandinos Zamfes, Chris Smart, Steve Zamfes
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... of a conventional swell test for four distinctive behaviors of the shale: non-swelling, nonlinear swelling, linear swelling and periodical swelling. Each...
2016
Abstract: Strategies to Include Geological Knowledge in Full Waveform Inversion; #90255 (2017)
Siddharth Sharma, Dries Gisolf, Stefan Luthi, Runhai Feng
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... after every iteration. This leads to a guided, nonlinear inversion process, where a geological scenario is proposed between two linear iteration...
2017
Abstract: Microseismic Estimates of Surface Seismic Brittleness Estimates: Application to a Barnett Shale Survey; #90309 (2017)
Roderick Perez-Altamar, John Henry Alzate, Amanda Trumbo, Kurt Marfurt
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... stage landed in a brittle, TOC-rich zone exhibited low gas flow. Furthermore, the generation of fractures is a nonlinear phenomenon. Examining...
2017
Abstract: Fast-Track and Robust Reservoir Modeling Using Probabilistic Neural Network; #90319 (2018)
Islam A. Mohamed, Basem K. Abd El-Fattah
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... change. The neural network inversion gained popularity over the last decades for its ability to establish nonlinear relationships between...
2018
Abstract: Feasibility of Moment Tensor Inversion for a Single-Well Microseismic Data Using Neural Networks; #90319 (2018)
Oleg Ovcharenko, Jubran Akram, Daniel Peter
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...-posed problems. We solve a nonlinear regression problem using a feedforward network, which is trained using a synthetic dataset from a homogeneous...
2018
Abstract: Predicting Brittleness for Wolfcamp Shales Using Statistical Rock Physics and Machine Learning;
Jaewook Lee, David Lumley
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.... Machine learning techniques can help to solve complex and nonlinear problems using large data sets. First, we conduct bivariate correlation analysis...
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Abstract: Near-surface Velocity Modeling through a Computationally Efficient Implementation of 1.5D Laplace-Fourier Full Waveform Inversion; #91204 (2023)
Apostolos Kontakis, Diego Rovetta, Daniele Colombo, Ernesto Sandoval-Curiel
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... information in the inversion process. The objective function is minimized by a nonlinear conjugate gradients, producing a single 1D velocity model per...
2023
Predicting Log Properties from Seismic Data Using Abductive Networks
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