.... Estimation methods offer a deterministic ‘best guess’ based on available data; kriging is a well-known technique in this category. Simulation methods generate various plausible scenarios, termed ‘realizations,’ without asserting the accuracy of any single outcome over others. These approaches, like Markov...

... intelligence machine learning sedimentary geology realization reservoir characterization geostatistical model modeling generative adversarial network geologic model geo-conditioned gan deep learning neural network transitional environment delta environment stratigraphy depositional environment...

... realizations and surface concepts, generates a range of possible outcomes, quantifies risk, and enables better decision making. This paper covers: The multi-discipline novel data analysis to characterize the reservoir and define the uncertainties The utilization of multiple geological realizations...

... The use of coarsened reservoir models provides the capability to balance between improved computational efficiency and preserving reservoir characteristics, especially barriers, connectivity and fluid distributions. For models with multiple geologic realizations, the generation of coarse models...

... subdiscipline multi-well inversion poisson unconventional reservoir strain kinematic history petroleum engineer unconventional asset realization novel methodology geomechanical model upstream oil & gas workflow inversion information capture anisotropy society Introduction The role...

... artificial intelligence realization ai-driven multiwell placement evaluation prediction asset and portfolio management uae government configuration abu dhabi well placement optimization Introduction Applying Machine Learning models to tackle the well placement optimization problem is not new...

... to execute the oil production project within 5 years including all operating & utility facilities. The TIME is the main contracting strategy driver of the Bisat project, which shall make sure early oil production, and cash realization for the shareholders. we can find that TIME is an essential criterion...

.... Once the training is performed, the model is deployed on a much larger ensemble with validation of random realizations using the physical simulator. We present results on a heterogenous three-dimensional subsurface model and highlight the potential benefits of PIML models, including reduced...

... intelligence fracture bayesian inversion giant fractured carbonate reservoir europe government reservoir simulation uae government multiplier workflow petroleum play type reservoir characterization unstructured grid complex reservoir generalized sensitivity analysis realization representation...

... and generation of high-resolution porosity realizations in the reservoir model. The multi-realization down-scaling workflow provided porosity realizations at the fine grid scale that fit the seismic information and can be further used in geomodelling workflows. The initial step of this integrated study workflow...

... modeling & simulation artificial intelligence history simulator optimization workflow ai-assisted history matching application ensemble abu dhabi uae government realization optimizer onshore carbonate reservoir Introduction Dynamic reservoir model calibration, also called history...

... learning neural operator saturation fno-tl prediction reservoir simulation subsurface storage shale gas enhanced recovery prediction realization climate change forecasting fourier neural operator application injection requirement Introduction Geological carbon storage in deep saline...

.... The forecasting workflow is evaluated on 3000 realizations of hydraulically fractured horizontal well placed in a complex heterogeneous shale reservoir. Each realization represents a condensate shale reservoir consisting of 88200 grid cells with spatially heterogeneous distributions of porosity, permeability...

... petroleum geology interpolation economic geology realization stationarity hypothesis organic matter source rock geological subdiscipline variogram probabilistic assessment histogram stratum geochemical characterization strata pyrolysis variability toc interpolation shale hydrocarbon...

... fluids. Identification and quantification of subsurface uncertainties were performed. These uncertainties were included in the geomodel for each scenario, which generated an ensemble of realizations and corresponding production forecasts. Two sets of economic results were produced—a simple, discounted...

... of project financing – Funding prerequisites – Funding possibilities Key factors for a successful project implementation Conclusion / future perspectives upstream oil & gas requirement petroleum engineer customer strategic planning and management realization presentation...

... a deep-learning, machine-learning (ML) model with an optimizer to automate the history-matching process. Initially, the reservoir simulator is run to generate an ensemble of realizations to provide a comprehensive set of data relating the history-matching uncertainty parameters and the associated...

... realizations and, therefore, not robust considering the reservoir characterization uncertainties. Increasing efforts were put into incorporating the uncertainties as a key element of the infill well placement workflow by computing probability maps to identify the hotspots with higher chances of success...

... approach from static to simulation with fast data assimilation and economic evaluation of possible scenarios proved to be key to reach all of these objectives. fluid dynamics ensemble risk management machine learning realization permeability history matching asset and portfolio management...

... for parameterization adds bias to the model calibration process, hence negatively impacting its outcome. In an era where ML/AI algorithms are shaping data interpretation methods, key modelling decisions can be revisited to realize the maximum value of subsurface data. However, a framework is required whereby...