... a predictive machine-learning model (consisting of a multiple linear regression model and a simple neural network). This model has been implemented successfully in field developments to optimize child-well placement and has enabled improvements in performance predictions and net present value. Introduction...

... to improve our understanding and prediction of downhole chemical reactions. In another featured study, a geochemical data set of staggering proportions was populated with water composition data from many years and wells. Coupled with the equations that govern many downhole reactions to use machine learning...

... Copyright 2021, Society of Petroleum Engineers fluid dynamics artificial intelligence relative permeability flow in porous media machine learning asia government reservoir characterization corey coefficient simulation saturation coefficient prediction schlumberger upstream oil & gas...

... at these times of opportunity. The potential operating states are constrained by a set of hierarchical rules defined by subject-matter experts, learnings from integrated diagnostics pilots, and basin-specific engineer knowledge. Pressure Prediction. To estimate the cost effect and understand the viability...

...-pressure prediction, wellbore-stability analysis, well-trajectory optimization, and sanding prediction. 1D Geomechanical Modeling To analyze wellbore stability, well logs, laboratory test results, and drilling reports of the wellbore were used to determine geomechanical characteristics of the drilled...

... simulation phm reservoir characterization prediction hydraulic fracture modeling hydraulic fracturing delaware play help optimize fracturing geometry geometrical constraint work flow ultrafast hydraulic field measurement fracture geometry field data TECHNICAL PAPERS | History Matching...

...Chris Carpenter _ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 206221, “Casing Wear: Prediction, Monitoring, Analysis, and Management in the Culzean Field,” by Florian Aichinger, SPE, Loic Brillaud, SPE, and Ben Nobbs, SPE, H&P Technologies...

.... It is important to have a model that will predict BHA directional tendency accurately. Traditionally, physics models were used to quantify the response and qualify the trajectory plan. While physics models can provide very accurate tendency predictions with the help of historical operations data, the prediction...

... mentioned above. I hope you find them as informative and transformational as I did. Recommended additional reading at OnePetro: www.onepetro.org. SPE 208174 Accurate Pore Fluid Indicator Prediction Using Seismic Fluid Bulk Modulus Inversion by Makky Sandra Jaya, Petronas, et al. SPE 211627 Seismic Motion...

... areas near low-confidence faults, affecting well performance and ultimate recovery predictions. To improve reservoir characterization and enhance field-performance predictions, a full-factorial 3D static Earth model was built by integrating well, surveillance, and seismic data. Dynamic simulation...

... overstimulation prediction multi-stage fracturing energy economics calibration intensity asset and portfolio management optimize vaca muerta well spacing objective eur TECHNICAL PAPERS | Hydraulic Fracturing Modeling Cloud Computing Optimizes Vaca Muerta Well Spacing, Stimulation Design Well spacing...

...; and Omar Mahmoud, SPE, Future University in Egypt. The paper has not been peer reviewed. _ The main objective of this work is to use machine-learning (ML) algorithms to develop a powerful model to predict well-integrity (WI) risk categories of gas-lifted wells. The model described in the complete paper can...

... better assessment of economic viability and producibility in frontier basins and the capability to identify bypassed pay in old wells that may not have rock material. The complete paper presents agile technologies that integrate data management, data-quality assessment, and predictive machine learning...

...Chris Carpenter _ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 205935, “From Wellbore Breakout to Sand-Production Prediction: An Integrated Sand-Control Completion Design Methodology and Case Study,” by Caleb DeValve, Gilbert Kao, SPE, and Stephen...

...Chris Carpenter This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 31758, “Downhole Pressure Prediction for Deepwater Gas Reservoirs Using Physics-Based and Machine-Learning Models,” by Jincong He, SPE, Matthew Avent, and Mathieu Muller, Chevron, et al...

... International Drilling Conference and Exhibition cardiology operation upstream oil & gas artificial intelligence participant technical paper health psychological factor machine learning rig training prediction strap drilling operation algorithm hrv accuracy vascular disease health...

...Chris Carpenter This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 203033, “Prediction of Fluid Flow in Porous Media Using Physics-Informed Neural Networks,” by Muhammad M. Almajid, SPE, and Moataz O. Abu-Alsaud, SPE, Saudi Aramco. The paper has...

... historical cases for use. However, the use of historical data for prediction of downhole accidents in the well-construction process is not a novel approach. It has been used in the industry for more than 30 years. The complete paper includes an extensive discussion of examples in the literature. 1 5...

... and permanent downhole gauges. A forecast study was conducted to validate the history-matched ensemble. The results showed a good match of 12 months of the new production data not used in history matching, which highlights the robust prediction capabilities of the approach. Geology of the Study Area Because...

... at the end of linear flow (time to depletion), estimate drainage volume, and predict the estimated ultimate recovery (EUR) of wells. RTA uses a rate-normalization technique to characterize how the well rate changes with a changing bottomhole flow pressure. However, rate normalization approximates a more...