... + f α j e w k ] . Note that we use Eqs. 6a and 6b in cases we history match total flow rate data given the BHPs in all wells. On the other hand, we use Eqs. 7a and 7b when match available BHP well data given the total liquid production rate data. For instance, the data...

... framework to a synthetic, yet realistic, field optimization problem using multiple history-matched realizations of the geologic model. For the synthetic realistic field example, the reservoir is assumed to undergo production for several years. Well controls (BHPs for producers and water injection rates...

... in interpretation. The objective of this paper is to develop an integrated artificial intelligence (AI) assisted workflow to calibrate uncertain parameters and automatically history match field-measured strain responses and then estimate the well production performance. The workflow is summarized as follows: First...

... In this study, we introduce a Deep Neural Network-based History-Matching (DNN-HM) workflow designed to enhance efficiency and scalability for addressing large-scale and complex history-matching problems. Our method integrates two tailored deep neural networks: a DL-based forward surrogate model...

... In this work, we present a tightly-coupled approach that combines the use of surrogate AI models and ensemble-based iterative optimization algorithms to enhance the history matching process. The efficiency of the hybrid approach is demonstrated on modified NORNE and BRUGGE benchmark models...

... need a rough prior model to start with and the calibrated model is not required, which significantly reduces the manual effort in history matching. In addition, as the training and prediction are very fast to perform, the same procedure can be repeated for multiple prior realizations in quite short...

... reserves in situ ( Ifticene et al. 2023 ; Salahshoor and Afzal 2022 ). unconventional play geology complex reservoir optimization problem petroleum play type modeling & simulation geologist reservoir simulation reaction artificial intelligence history matching steam-assisted gravity...

... count and having too many connections could potentially lead to over-fitting in history matching, the best practice usually requires using the above-mentioned three parameters in a trial-and-error approach. Interested readers can refer to Guan et al. (2023) for a detailed discussion on how to choose...

... to historical production data. In this work, an ensemble of conditional realizations is generated by a multi-realization history-matching (MHM) workflow. The posterior probability-density-function (PDF) of model parameters and/or production forecasts is non-Gaussian and we approximate it by a Gaussian-mixture...

... Abstract Surrogate modeling is essential in reducing computational costs for history-matching applications. Yet, traditional deep learning-based surrogate models cannot cope with high dimensional input parameters, such as the permeability field. This work introduces a robust method to automate...

...) models, which are integrated with a multi-proxy-based Markov Chain Monte Carlo (MCMC) algorithm to generate the history matching solutions and posterior distributions of the uncertain parameters that quantify the uncertainty of the resultant fracture geometry and assess the stimulation/completion...

... than the molecular tracers, or both polymeric and molecular tracers may breakthrough at a similar time. Ensemble smoother with multiple data assimilation with tracer data (ES-MDA-Tracer) algorithms were then used for history matching and predicting the inter-well porosity. Encouragingly, including both...

... Abstract An ensemble of rigorously history matched reservoir models can help better understand the interactions between heterogeneity and fluid flows, improve forecasting reliability, and locate infill-drilling opportunities to support field development plans. However, developing efficient...

... history matching deep learning flow in porous media asia government artificial intelligence neural operator complex reservoir prediction gravity drainage modeling & simulation numerical simulation society sagd reservoir simulation petroleum play type heavy oil play architecture...

... harnessing of energy produced by microbes from hydrogen and electricity. The challenge is the efficiency of the processes that are limited in scope. This limits the amount of hydrogen to be produced efficiently ( Katterbauer, Hoteit and Sun, A Time Domain Update Method for Reservoir History Matching...

... physics-based data-driven model referred to as INSIM-BHP for reservoir flow and transport as a replacement for a reservoir simulator. INSIM-BHP provides rapid and accurate computation of well rates and BHPs for history matching, forecasting, and production optimization purposes. INSIM-BHP delivers precise...

... analysis and modeling. air emission history matching drillstem/well testing upstream oil & gas fluid dynamics pressure transient testing neural network subsurface storage structural geology modeling & simulation reservoir simulation gas injection method flow in porous media...

... Abstract Full history match models in subsurface systems are challenging due to the large number of reservoir simulations required, and the need to preserve geological realism in matched models. This drawback increases significantly in big real fields due to the high heterogeneity...

... was developed to generate multiple history matched models on field and well level. Static reservoir characteristics and contacts where parameterized for sensitivity assessments and calibration update steps. Variations of dynamic reservoir characteristics with an impact on model forecasting behavior were applied...

... assumptions that cannot be generalized for three-phase flow or when relative permeability is unknown. In this study, a new RTA-assisted history-matching technique is proposed to simultaneously match production data and diagnostic plots during the calibration process. In the proposed method, the objective...