Generative Adversarial Networks (GANs) have shown impressive results for image
generation. However, GANs face challenges in generating contents with certain types of …

With the aid of machine learning method, namely artificial neural networks, we established
data-driven proxy models that could be utilized to maximize the net present value of a …

We develop a framework based on the lexicographic method and the newly developed
Stochastic-Simplex-Approximate-Gradient (StoSAG) algorithm to maximize the expected net …

We develop a proxy model based on deep learning methods to accelerate the simulations of
oil reservoirs--by three orders of magnitude--compared to industry-strength physics-based …

Proxy models are derived mathematical functions developed as substitutes for reservoir flow
simulators. Several types of proxy models are reported in the literature, for instance …

Traditionally, fractured reservoir simulations use Dual-Porosity, Dual-Permeability (DPDK)
models that can idealize fractures and misrepresent connectivity. The Embedded Discrete …

This study examines the application of pattern recognition technologies to improve the time
and effort required for completing successful history matching projects. The pattern …

In oil production optimization, we usually aim to maximize a deterministic scalar
performance index such as the profit over the expected reservoir lifespan. However, when …

The complex and unique production mechanism of CBM has been examined extensively;
however, production from such reservoirs requires more investigation to be well-understood …

An integral aspect of smart reservoir management of oil and gas fields is the process of
identifying and performance forecasting of the remaining, feasible, and actionable field …