MEDIA
Publications
Machine Learning Applications to Improve Pore Pressure Prediction in Hazardous Drilling Environments
Pore pressure analysis can be imperative while drilling, especially in certain offshore environments where abnormal pore pressures can cause serious problems such as fluid influx, kicks, and blowouts. In order to avoid such events, the prediction in real-time, or preferably…
Approach Evaluates Geothermal Potential in Existing Oil and Gas Wells
In the complete paper, the authors discuss an integrated cloud-based work flow aimed at evaluating the cost-effectiveness of adopting geothermal production in low- to medium-enthalpy systems either by repurposing existing oil and gas wells or by coproducing thermal and fossil…
Asset Re-Purposing Feasibility for Geothermal Energy Production in Ukraine
According to the new energy strategy in Ukraine, the production of electricity from alternative sources should increase to 25-30% till 2030 and geothermal energy should make up 2% of the total energy supply. The expected installed capacity of geothermal energy…
Real Time Cloud-Based Automation for Formation Evaluation Optimization, Risk Mitigation and Decarbonization
Recent developments in artificial intelligence (AI) have enabled upstream exploration and production companies to make better, faster and accurate decisions at any stage of well construction, while reducing operational expenditure and risk, increasing logistic efficiencies. The achieved optimization through digitization…
Is Decline Curve Analysis the Right Tool for Production Forecasting in Unconventional Reservoirs?
This study presents a novel metaheuristic algorithm that uses a physics-based model for multi-fractured horizontal wells (MFHW) to accurately predict the estimated ultimate recovery (EUR) for unconventional reservoirs. The metaheuristic algorithm creates a sizeable number of stochastic simulations and keeps…
Geothermal Production from Existing Oil and Gas Wells: A Sustainable Repurposing Model
The geothermal energy industry has never quite realized its true potential despite the seemingly magical promise of nonstop, 24/7 renewable energy sitting just below the surface of the Earth. In this paper, we discuss an integrated cloud-based workflow aimed at…
How Deep Learning can Provide Consistent Improvement on ROP Through Different Drilling Environments
Using multidimensional analysis of historical drilling parameters combined with deep learning (DL) techniques, consistent ROP improvement in different drilling environments can be achieved. This discussion is focused on how offset well data can be properly analyzed and modeled to generate…
Artificial Intelligence for Production Optimization in Unconventional Reservoirs
This work presents two cases for the application of artificial intelligence (AI) techniques as complementary tools to classic physics-based modeling. On the one hand, we discuss the benefits from the implementation of an AI-assisted non-linear solver, especially designed for analytical…