... across the industry. modeling & simulation composition variation equation of state reservoir characterization reservoir equilibration upstream oil & gas artificial intelligence initialization compositional variation reservoir simulator reservoir model initialization ghorayeb...

... 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...

... with the commercial reservoir simulator as a final validation step. Abstract Leveraging the recent developments in the Machine Learning (ML) technology, the objective of this work was to use Artificial Neural Networks to build proxy models to classical reservoir simulation tools for two distinct chemical EOR...

... 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...

... 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...

...Introduction Abstract Chemical enhanced oil recovery (CEOR) techniques are some of the most effective and economical tertiary oil extraction processes. As a key tool for the recovery performance evaluation, reservoir simulation plays an instrumental role in the expansion of the field...

... Reservoir simulation is required to aid in the decision-making for high-impact projects. It is a culmination of geophysical, geological, petrophysical, and engineering assessments of sparse, uncertain, and expensive data. History matching is a process of elevating trust in numerical models...

.... An integrated hydraulic fracturing and reservoir simulator that has been developed at the University of Texas at Austin is utilized for this study. The simulator is a non-isothermal, multi-phase black-oil flow in reservoir, fracture, and wellbore domains. It was found that using thermally controlled fluid...

... 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...

... presents proposed methods for selected devices, and device models supported by simulations. The proposed methods show the potential for qualified benchmarking of Inflow Control Technology (ICT) completed wells in dynamic reservoir simulations compared to the generic models currently in use. New single...

... on a dynamic model and its impact is examined using a reservoir simulator. In the second phase, this approach is applied only for gas producers, and in the third phase the smart completions are simultaneously applied to both water injectors and gas producers. The detailed study has revealed...

... and/or a reservoir simulator. The process starts with the integration of a wide range of production and reservoir engineering data types from multiple sources. Following this, a series of monitoring and surveillance dashboards of key units and elements of the entire waterflood operations are created. The workflows...

... and VL conditions of a coal core. A prior study by Ramsay and Hinkley (2017) has shown the effect of flow condition on upscaled relative permeability for a composite coal core using process control automation in a reservoir simulator ( Landmark 2019 ). That study demonstrated that upscaled steady...

... Abstract Reservoir simulation models that represent large-sized reservoirs require significant use of High-Performance Computing resources. Several solutions aim to reduce the load of an individual simulation such as upscaling to consequently reduce the number of grid cells of the model...

... Abstract In discrete upscaling methods, the saturation history of corefloods is often lost, while automated upscaling methods retain the saturation history of corefloods. A reservoir simulator is used to upscale imbibition relative permeability using discrete and automated methods. Both...

... Abstract The popularity of parallel reservoir simulation has increased in recent years due to availability of multi-core CPUs and the opportunity for run-time reduction, especially in complex and fractured reservoir models that include large amounts of data. However, the accuracy of classical...

... Abstract History matching (HM) is a mandatory step for any reservoir simulation study. Without a proper history match, a reservoir simulation model may lose credibility, or even worse, may lead to erroneous conclusions. HM is typically approached by reservoir enginners (RE) using a trial...

... facilities; linking reservoir simulator at IPR Level, through in-house simulation model developed in commercial simulator. Keeping in view the target of study i.e. incremental and sustained production, reservoir rates were constrained and hence semi-implicit approach was used instead of fully implicit...

... Abstract This paper presents an innovative application of the Integrated Asset Model (IAM) approach for simulating a surface network collecting many fields on production and multiple constraints, using a last-generation High-Resolution Reservoir Simulator (HRRS) applied to low-permeability...

... Abstract Reservoir simulation is becoming increasingly complex because of more advanced wells in the fields, including intelligent and multilateral wells. Advanced completions are also evolving to increase recovery efficiencies. This increasing complexity presents two difficulties, which...