... scenarios proved to be key to reach all of these objectives. fluid dynamics ensemble risk management machine learning realization permeability upstream oil & gas flow in porous media artificial intelligence workflow facies reservoir simulation modeling & simulation reservoir...

... of high remaining mobile hydrocarbons and good reservoir rock quality to be targeted. The identification of hotspots was also largely performed on single-model realizations and, therefore, not robust considering the reservoir characterization uncertainties. Increasing efforts were put into incorporating...

... for optimizing and evaluating ensemble-based infill well locations. An opportunity index (OI) is derived from static and dynamic grid properties of reservoir simulation and a connected component search for every realization. Probability maps of OI are constructed to present the likelihood of high-OI areas from...

... upstream oil & gas neural network realization prediction mismatch reservoir simulator history matching artificial intelligence workflow deep-learning-based surrogate reservoir model autoencoder result optimizer ml engine physics-based reservoir simulator iteration optimization...

... engineer customer project management hydrogen project implementation criteria financing strategic planning and management realization presentation functionality transparency coordination partnership society spe-210958-ms engineering evaluation specialist Partnerships in hydrogen...

... and efficient way of analyzing static model realization results in a more visual, interactive and efficient manner allowing a multidisciplinary team to absorb information and key ideas quickly. The proposed methodology starts with a set of properties from a given static grid realization. The data are prepared...

... representative model. This helps de-risk drilling the new wells in the new anticline. This workflow took less than 1 month to generate more than 3000 realizations instead of just a single realization using the traditional approach. The workflow can be summarized in the following processes: Abstract...

... real-life application. The process is applicable on single or multi-realization models (considering uncertainties). Thanks to the intuitive nature of WISH design rules, human easily keep control of overall optimization during the exploration loops. Performing patterns are identified in looping...

... 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...

... eod fluid dynamics water saturation workflow algorithm realization different reservoir input data ensemble artificial intelligence upstream oil & gas modeling approach production history complexity history matching history matched ensemble permeability petroleum engineer initial...

... primary production upstream oil & gas gravity drainage fracture complex reservoir presented matrix block reservoir realization matrix permeability enhanced recovery recovery process prediction sensitivity analysis fractured reservoir fracture model permeability oil recovery...

... of the predicted high-resolution elastic attributes in the depth static model. Rock physics modeling and Bayesian classification were used to convert the elastic properties into porosity and lithology (static rock-type (SRT)), which were validated in blind wells and used to rank the multiple realizations...

... midstream oil & gas blowdown workflow ensemble indicator upstream oil & gas key performance indicator modeling uncertainty development team realization forecast Modeling Uncertainty in Field Development Scenarios In field development planning, many decisions should be made...

... definition of the mismatch between the initial ensemble simulation results and the historical data used by ensemble algorithms. In fact, a notion of distance among ensemble realizations can be introduced using the mismatch, opening the possibility to use statistical analytic techniques like Multi-Dimensional...

... workflow realization th iteration hm target scalar parameter initial ensemble Introduction Ensemble History Matching (EHM) methodologies are founded on the idea that a full set of model realizations should be used (instead of a single model) to quantify and propagate the model uncertainty...

... production data realization identification optimizer Introduction The oil and gas business, like the rest of the globe, is evolving. Companies must adapt and be ready to withstand the test of time like never before - by being productive, agile, and ahead of the curve. Operationalizing model-based...

... to multiple hotspot regions under technical and economic constraints. A structured workflow design is applied to a multi-layered/stacked reservoir model. Subsurface uncertainties are described and captured by multiple model realizations, which are constrained in areas of historical wells. An infill well...

... parameter rock type reservoir characterization upstream oil & gas structural uncertainty workflow interpretation realization reservoir reference case top reservoir historical pressure data Introduction Main objectives for any Exploration and Production company is to estimate...

... on individual basis and ultimately combine them into a realization that meets all these criteria and direct observations from available data. The workflow here presented establish a sequence of steps to fulfil all these requirements in a simple way. Progression of the data integration carries consistency across...

... 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...