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West Virginia University

Theses/Dissertations

Artificial Intelligence

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Full-Text Articles in Engineering

Synthetic Well Log Generation Software, Daniel E. Keller Jan 2023

Synthetic Well Log Generation Software, Daniel E. Keller

Graduate Theses, Dissertations, and Problem Reports

In this study, we developed a novel approach to generate synthetic well logs using backpropagation neural networks through the use of an open source software development tool. Our method predicts essential well logs such as neutron porosity, sonic, photoelectric, and resistivity, which are crucial in various stages of oil and gas exploration and development, as they help determine reservoir characteristics. Our approach involves sequentially predicting well logs, using the outputs of one prediction model as inputs for subsequent models to generate comprehensive and coherent sets of well logs. We trained and tested our models using 16 wells from a single …


Utilization Of A Numerical Reservoir Simulation With Water And Gas Injection For Verification Of Top Down Modeling, Ashley Konya Jan 2020

Utilization Of A Numerical Reservoir Simulation With Water And Gas Injection For Verification Of Top Down Modeling, Ashley Konya

Graduate Theses, Dissertations, and Problem Reports

The primary purpose of this thesis was to confirm the capabilities of artificial intelligence and machine learning through Top Down Modeling in history matching and predicting the oil, gas, and water production rates, reservoir pressure, and water saturation, of one limb of an anticline with water and gas injection. Several other characteristics were also applied to make the model more realistic to industry standards. The second purpose of this thesis was to determine the minimum amount of training and calibration data required in order to obtain good results for this particular dataset by increasing the blind validation in one year …


Top-Down Model Development Using Data Generated From A Complex Numerical Reservoir Simulation With Water Injection, Yvon Andrea Martinez Jan 2020

Top-Down Model Development Using Data Generated From A Complex Numerical Reservoir Simulation With Water Injection, Yvon Andrea Martinez

Graduate Theses, Dissertations, and Problem Reports

Numerical simulation and data-driven modeling are two current approaches in engineering reservoir modeling. Numerical reservoir simulation attempts to match past production history by modifying reservoir properties of the model. After multiple computationally intensive trial and error efforts, accurate history matches are identified. These history matches are used by project management for production forecasting purposes. Data-driven reservoir modeling utilizes measured data and is, therefore, free of assumptions that are often included in numerical reservoir simulations. Artificial intelligence and machine learning algorithms are technologies implemented in the development of a data-driven reservoir model with efforts to learn fluid flow through porous media …


Application Of Machine Learning On Fracture Interference, Dennis Wayne Chamberlain Jr. Jan 2018

Application Of Machine Learning On Fracture Interference, Dennis Wayne Chamberlain Jr.

Graduate Theses, Dissertations, and Problem Reports

A method has been developed that locates and determines well-to-well hydraulic fracture interference (frac-hit) in shale plays using hard data. This method uses Artificial Neural Networks (ANN) with designated parameters and target outputs in conjunction with graphs of gas flowrate, tubing pressure, and cumulative gas prediction. The method was created to address the significant increase in frac-hit occurrences due to the infill wells being completed in shale plays. The production data of the well is first cleaned to eliminate outliers in the initial timeframe of the well and periods of no production so that the ANN model can be accurately …