mobile regnow

morning token content

Morning Presentations

Controls on Stratigraphic Evolution and Distribution of Organic Carbon Content and Type in the Reservoir Shale of the Lower Permian Whitehill Formation of South Africa
K. Chukwuma1, H. Tsikos1, N. Wagner2 (1Rhodes University; 2University of Johannesburg)
Geological Controls of the Organic-Inorganic Distributions within the Woodford Shale in Oklahoma USA: Integrating for Finding the Unconventional Sweet Spots
E. J. Torres, A. Liborius-Parada, S. Sinha, R. Slatt, K. J. Marfurt (University of Oklahoma)
Organic Matter Type Identification and Thermal Maturity Estimation using Raman Microscopy
L. A. Hathon1, Z. Liu2, M. T. Myers1 (1University of Houston; 2Halliburton)
Transfer Learning for Scalable Optimization of Unconventional Field Operations
H. Klie, B. Yan, A. Klie (DeepCast.ai)
Managing Well Design and Planning Workflows in Digital Well Programs using Hash-Pointer-Linked Lists
P. Kowalchuk (Halliburton)
Field Development Strategy using Mixed Data Sources: An Application of Data Analytics to Eagleford Development
A. Selveindran, P. Chen (University of Houston)
A Data-Driven Workflow for Optimizing Shut-In Strategies of Adjacent Wells During Multi-Stage Hydraulic Fracturing Operations
A. Shahkarami, H. Stephenson, R. Klenner, G. Murrell (Baker Hughes)
Basin-Specific Machine Learning Models for Efficient Completions Optimization
C. R. De Sario1, A. Bogdan1, D. Fu1, S. Khan1, J. Nabors2, T. Voss2 (1BJ Services, LLC; 2Spur Energy Partners)
Oil Swelling Measurement Techniques:Conventional Methods and Novel Pressure-Based Method
S. Fakher1, Y. Elgahawy2, H. Abdelaal3 (1Missouri University of Science and Technology; 2University of Calgary; 3University of Lisbon)
Normal 0 false false false EN-US ZH-CN X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:普通表格; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Arial",sans-serif; mso-fareast-language:EN-US;}Application of Liquid Nanofluid during HydraulicFracturing in Tight Reservoirs
X. Liang, T. Liang, F. Zhou, S. Yuan (China University of Petroleum at Beijing)
Oil-Water Two-Phase Flow Behavior in Shale Inorganic Nanopores: From Molecule Level to Theoretical Mathematical Model
S. Zhan2,1, Y. Su1, Z. Jin2, W. Wang1, L. Li1, (1China University of Petroleum (East China); 2University of Alberta)
Proximal to Distal Variability of Mississippian Lithofacies, Depositional Environments, Diagenetic Processes, and Reservoir Quality within a Mixed Siliciclastic-Carbonate System, Eastern Anadarko Basin, Oklahoma, USA
F. Suriamin, M. J. Pranter (School of Geoscience)
Comparison of Wireline Log and SEM Image-Based Measurements of Porosity in Overburden Shales
C. J. Landry1, B. Hart2, M. Prodanović1 (1University of Texas at Austin; 2Equinor)
Characterization of Three Forks Formation Reservoir Lithofacies in the Williston Basin, North Dakota
A. Adeyilola1, S. Nordeng2, C. Onwumelu2, O. Tomomewo2 (1Central Michigan University; 2University of North Dakota)
Estimation of Orthorhombic Elastic Properties of Thinly Laminated Rocks using Plane and Point Transducers in Cylindrical Samples
G. Gallardo Giozza1, D. N. Espinoza1, C. Torres-Verdín1, E. Maalouf2 (1The University of Texas at Austin; 2American University of Beirut)
Enhancing PSDM via Well Data Derived from Gradient Boosted Trees Machine Learning
M. Rauch, M. Perz, S. Namasivayam, A. Sharma (TGS)
Seismic Quantitative Analysis for Physical-Based Deep Learning: The Teapot Dome and Niobrara Shale Examples
N. Martin (CLS GeoSolutions LLC)
Optimizing Eagle Ford Development through Integrated Earth Modeling
R. Kommaraju (Penn Virginia Oil & Gas)
Improved TOC and Lithology Prediction for Wolfcamp Shales Using AVO Attribute Analysis
J. Lee1, U. Y. Lim2, D. Lumley1 (1University of Texas at Dallas; 2Chevron Energy Technology Company (formerly, Texas A&M University))
Predicting Fluvial Reservoir Facies by Upscaling Seismic Inversion with 3-D Geocellular Modeling: Pinedale Field Case Study
S. K. Logan1, E. LaBarre1, C. Dorian2, P. R. Clarke1, M. Ahmed3, A. Hartley4 (1Ultra Petroleum; 2Schlumberger; 3CGG; 4University of Aberdeen)
Assessment of Complex Fracture Networks Effect on Rate Transient Behavior Using Embedded Discrete Fracture Model
J. Qin1, S. Cheng2, W. Yu1, J. Leines1, K. Sepehrnoori1 (1The University of Texas at Austin; 2China University of Petroleum-Beijing)
Deriving Time-Dependent Scaling Factors for Completions Parameters in the Williston Basin using a Multi-Target Machine Learning Model and Shap Values
T. Cross, D. Niederhut, K. Sathaye, K. Darnell*, K. Crifasi (Novi Labs)
Multi-Segment Hyperbolic Model Improves Production Forecasts in Permian Basin Volatile Oil Wells
B. C. Sherman, J. Lee (Texas A&M University)
An Integrated Multi-Disciplinary Modeling and Simulation Approach to History Matching and Forecasting Shale Wells — An Eagle Ford Case Study
U. Aslam, R. Bordas (Emerson Automation Solutions)