..., perform a time series regression to identify the structure of the elements in that row, and their values. This involves a feature selection algorithm. Integrate these estimated DAE equations, and compare results with the original. Initial history match using reservoir simulator We use two...

... Abstract The data-driven interwell simulation model (INSIM) has been recognized as an effective tool for history matching and interwell-connectivity characterization of waterflooding reservoirs. INSIM-FT-3D (FT: front tracking) was recently developed to upgrade the applicationdimension of INSIM...

... they are with respect to a certain response variable. Abstract Design of Experiments (DoE) is one of the most commonly employed techniques in the petroleum industry for Assisted History Matching (AHM) and uncertainty analysis of reservoir production forecasts. Although conceptually straightforward, DoE is often...

... Abstract The use of deep-learning-based procedures for geological parameterization and fast surrogate flow modeling may enable the application of rigorous history matching algorithms that were previously considered impractical. In this study we incorporate such methods – specifically...

... and easy fault juxtaposition modification. This feature avoids the process of updating the structural framework and regenerating the reservoir properties, which may be time-consuming. To facilitate juxtaposition updates within an assisted history matching workflow, several parameterized fault throw...

... Abstract The Ensemble Smoother with Multiple Data Assimilation (ES-MDA) method has been popular for petroleum reservoir history matching. However, the increasing inclusion of automatic differentiation in reservoir models opens the possibility to history-match models using gradient-based...

... and portfolio management waterflooding injector formulation 3 application npv production control artificial intelligence drillstem testing upstream oil & gas olympus field producer optimizer reservoir surveillance optimization problem history matching priority function iteration...

... Abstract History matching is critical in subsurface flow modeling. It is to align the reservoir model with the measured data. However, it remains challenging since the solution is not unique and the implementation is expensive. The traditional approach relies on trial and error, which...

... Abstract When formulating history matching within the Bayesian framework, we may quantify the uncertainty of model parameters and production forecasts using conditional realizations sampled from the posterior probability density function (PDF). It is quite challenging to sample such a posterior...

... As mentioned above, history matching is a non-linear optimization process. Hence, there will be multiple models that fit the data. Pure geostatistical approaches may converge to a solution but not the solution. To remedy this shortcoming, we constrain the solution so that it follows...

... There is rich literature on various probabilistic history matching methods. Sampling-based algorithms include rejection sampling ( Caers, 2011 ; He et al., 2016 ) and Markov-chain Monte Carlo ( Chen et al., 2016 ; Hastings, 1970 ; Ma et al., 2008 ), which are relatively straightforward...

... Abstract In this work, we investigate different approaches for history matching of imperfect reservoir models while accounting for model error. The first approach (base case scenario) relies on direct Bayesian inversion using iterative ensemble smoothing with annealing schedules without...

... There has been a growing interest in enhancing reservoir characterization through history matching using EM observations. Katterbauer et al. (2016) presented a history matching study using EM data attribute (conductivity, assumed to be known) to estimate the components of a compositional...

... For cases where the subsurface uncertainties can be characterized by a list of continuous parameters, the calibration to pre-existing historical data can be accomplished by traditional probabilistic history-matching methods. Compared with deterministic history matching, probabilistic history...

... The workflow starts with plausible uncertain parameters and their pre-specified ranges. In order to improve the quality and efficiency of the history matching process, it is not recommended to calibrate all parameters at once. First, sensitivity analysis is conducted to identify key parameters...

... model and the procedure for history matching; (2) we introduce the method to perform production optimization with a history-matched INSIM-FT-3D model; (3) two synthetic examples including a field-scale synthetic reservoir model are presented; (4) finally some comments are given. Formulation of INSIM...

... Abstract The use of full-physics models in close-loop reservoir management can be computationally prohibitive as a large number of simulation runs are required for history matching and optimization. In this paper we propose the use of a physics-based data-driven model to accelerate reservoir...

... Abstract In this study we explore the use of multilevel derivative-free optimization for history matching, with model properties described using PCA-based parameterization techniques. The parameterizations applied in this work are optimization-based PCA (O-PCA) and convolutional neural network...

...History Matching We utilize a hierarchical approach to update the model parameters. Our history matching workflow consists of two stages: global and local. At the global stage of history matching, large-scale features such as regional permeabilities, pore volumes, faults transmissibility...

... Abstract Increased access to computational resources has allowed reservoir engineers to include assisted history matching (AHM) and uncertainty quantification (UQ) techniques as standard steps of reservoir management workflows. Several advanced methods have become available and are being used...