... Reservoir simulation is (mostly) memory bandwidth limited, i.e., performance is essentially governed by how fast data moves from memory to the arithmetic units rather than how fast these can perform calculations. For example, a good quality full-GPU simulator running on a single high end server...

... simulator configuration exhibition terminal constraint simulation reservoir asset and portfolio management quantity integrated asset model enhanced integrated asset model base case platform upstream oil & gas development case scenario integrated asset modelling separator...

.... Results, Observations, Conclusions The deep learning network was trained for inspecting the structure and monitoring the operation of the flare stack system. Simulations were conducted for evaluating the performance of the proposed structure and operation inspection technique and real images of flare...

... operators improve their margins, reduce their emissions and, in general, position themselves for sustainable growth. Before they are in operation, plants (and oilfields alike) are typically simulated using physics-based tools. In practice, therefore, physics-based simulation models pre-date any plant data...

...: Real-time flow rate prediction of various phases Real-time wells performance Real-time pipeline network performance The dynamic nature of the problem and the variability of the solution space makes it extremely hard for traditional simulation-based solutions to locate the optimal performance...

... an application of ML to develop surrogate reservoir models that are based on simple neural networks. The authors used inputs such as well identifiers, static reservoir properties, and dynamic data to predict annual oil rate production. These ML models were then used to replace a numerical reservoir simulator...

... Abstract Reservoir engineers tend to define a simulation model as "complex" when they have several of the following characteristics: Complex fluids schemes loaded with multi PVT's or EOS's data sets associated with lateral and vertical compositional changes that might cause massive fluids...

... Abstract Flash calculation is an essential step in compositional reservoir simulation. However, it consumes a significant part of the simulation process, leading to long runtimes that may jeopardize on-time decisions. This is especially obvious in large reservoirs with many wells...

... Abstract Prediction of the wellbore fluids and formation temperatures during well construction is an essential step for efficient drilling operation. This work presents the applications of an improved comprehensive drilling simulator for predicting the wellbore system temperature during...

... approach includes a simulation approach including MFRAC TM Simulator by Baker Hughes and GEM by CMG, a machine learning approach utilizing SpeedWise ® ML by QRI, and an economic evaluation approach utilizing NPV calculations. The workflow starts with the following steps: (1) data acquisition and data...

... flowmeter solution adopted by Al Yasat utilizes first principle based high fidelity multi-phase flow assurance simulator, leveraging its machine learning model for fast and robust flow estimation. Dynamic analysis and data driven approach of the virtual flow meter solution ensures the estimation accuracy...

... that control its performance might result in unfavorable oil recovery. Therefore, this study provides more insight into improving WAG oil recovery by optimizing different surface and subsurface WAG parameters using a coupled surface and subsurface simulator. Moreover, the work investigates the effects...

... of significant differences in modeling CO 2 storage sites compared with hydrocarbon reservoir simulations. These differences can greatly influence reliability when modeling CO 2 storage sites. climate change modeling storage site simulator ccus project simulation capillary force upstream oil...

... Abstract This paper presents a practical methodology of optimizing and building a detailed field surface network system by using the high-resolution reservoir simulator driven custom-made Python scripts to efficiently predict the future performance of the vast oil and gas-condensate carbonate...

... communication, simulation-based exercises and automated testing/certification. The program is divided into Master Development Planning (MDP) and Well & Reservoir Management (WRM) domains which are related to different stages of the petroleum asset lifecycle. The interaction with simulator takes 2-3 days...

... is a combination of an engineering workflow supported by geomechanical modeling and an advanced simulator of in-situ kinetics and materials transport to model the placement of a customized, impermeable mixture of particles that will restrict fracture growth. The optimized treatment design included injections...

... significantly to the optimization of production operations, and there is a trend towards hybrid AI , which combines data science with traditional physics-based simulators to deliver added value. In our work we show how to make use of physical principles in feature engineering to improve machine learning...

... matter and clay. The paper provides a detailed numerical simulation approach from a modified commercial simulators to simplify analytical solutions for adsorbed gas in-place calculation and full field development plan. The construction of dynamic model to tackle the growing advances in drilling...

... and contextualized, and combined with powerful simulation, analytics, and asset performance management (APM) tools to enhance performance, reliability, and maintenance. For illustrative purposes, an oilfield use case will be presented involving the implementation of a an open and flexible operational intelligence...

...Black Oil Model Abstract A great deal of computational power and time is necessary for simulating highly heterogeneous fractured reservoirs with complex geometry; the efficiency of these computations is a major subject especially in large-scale heterogeneous and fractured reservoirs. So...