... characterization scenario assimilation saturation evaluation history matching asset and portfolio management enhanced recovery field implementation initial ensemble abu dhabi posterior ensemble information probability ensemble workflow Introduction & Context Operators are continuously...

... for History Matching of this mature field. An integrated static and dynamic model was built for the first time for the entire south panel as apposed to independent simulation of single reservoirs. Abstract This paper discusses an integrated reservoir study utilizing structured and novel machine learning...

... history match process and reduce the range of uncertainties. There are many mature oilfields in offshore peninsular Malaysia with more than 40 years of production and more than 150 multi-layered completion strings per field. The multi-layered completion wells in stacked reservoirs are used to lower...

... With the rise of artificial intelligence (AI)/machine learning (ML) to solve various complex tasks, researchers in the oil and gas industry proposed different ways of leveraging ML to accelerate time-consuming and labor-intensive history matching workflows. Shahkarami et al. (2014) showed...

.... This paper describes an overall reservoir management workflow which consists of (1) the application of a novel data assimilation method for assisted history matching, and (2) the optimization of water-alternating-gas (WAG) injection cycles to maximize the life-cycle estimated ultimate oil recovery (EUR...

... levels history match profiles. Limited sources of data available with high levels of geological heterogeneity with multi-layers and patchy zones, which result in creating many thin layers that would tend to impact dynamic model performance. This paper is going to discuss the implementation steps...

... uncertainties pose challenges to history match and to conduct probabilistic forecast studies on the dynamic models. Conventionally, the development scenarios for subsurface investigation are limited due to finite computing resources. As PETRONAS is shifting its portfolios to develop more complex and challenging...

... 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...

.... In the elaborated enhanced oil recovery (EOR) evaluation process, a machine learning assisted approach is used in order to narrow geological and dynamic parameter ranges both for model initialization and subsequent history matching. The resulting posterior parameter distributions are used to create the input models...

... unreliable due to inconsistent property modifications during the history matching process, full span of prediction uncertainty isn't properly propagated for economic evaluation and the whole process is not fully automated. This paper presents an integrated and automated forward modelling approach where...

... for facies modeling and uncertainties are propagated in the dynamic response of the geologically plausible ensembles. These equiprobable models are then history-matched simultaneously using an ensemble-based conditioning tool to match the available observed field production data within a specified tolerance...

... Abstract Improvements in reservoir simulation computational time thanks to GPU-based simulators and the increasing computational power of modern HPC systems, are paving the way for a massive employment of Ensemble History Matching (EHM) techniques which are intrinsically parallel. Here we...

... with the largest impact on recovery, use of an experimental design methodology with a space-filling design resulted in alternative history matches. Statistical analysis of forecasts yielded probability density functions and low and high estimates of ultimate recovery. Forty-five uncertain variables, including...

... Abstract FGIIP (Field Gas Initially in Place) is one of the most essential elements in building dependable static and Integrated Asset Model (IAM). A good estimation of FGIIP will improve history matching and generate reliable forecast. The mature gas field producing under depletion mode...

... python script bcr oil price benefit-cost ratio development strategy optimization process economic parameter optimization problem upstream oil & gas economic model profitability water cut economic limit history matching efficiency cash flow model well economic limit injection year...

.... Abstract Reservoir model history matching is the solving process of a complex inverse equation mainly relating reservoir and well properties to observed data using a time and space discretized numerical model. A challenging task for engineers but a prerequisite to a vital tool to field development...

... deep learning neural network upstream oil & gas optimization artificial intelligence history matching opportunity index producer realization ensemble scenario probability society of petroleum engineers hotspot well location optimization probability map well location design machine...

... upstream oil & gas information complex reservoir wellbore design history matching pore pressure wellbore integrity flow in porous media drillstem testing drilling operation fracture characterization permeability model hydraulic fracture design fluid dynamics fracture design workflow...

..., production control and understanding major reservoir mechanisms, it is desirable to use a reservoir modeling methodology that is easy to build, history match, compute and interpret. In this work, we propose to use a hybrid and efficient reservoir graph network (RGNet) modeling approach based on time...

... Eq. 2 Σ ˜ R T − 1 = ( 1 / σ x ′ 2 0 0 1 / σ y ′ 2 ) In the new coordinate system along the principal directions ellipse equation Eq. 1 takes canonical form: Abstract Most history matching (HM) tools consider only...