1-20 of 76
Keywords: objective function
Close
Sort by
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203950-MS
...Bayesian Optimization Bayesian optimization has emerged as a powerful solution for control and optimization problems when the objective functions are expensive to evaluate or potentially intractable. Bayesian optimization has been shown successful in machine learning for hyperparameter tuning...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203971-MS
... the Pareto front by modifying the weighting factors of the weighted average of multi-objective functions ( Gal and Nedoma 1972 ). The other one is based on the concept of Pareto dominance and integrated with evolutionary algorithms, which constructs the Pareto front without requiring weighting factors...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193811-MS
... interpolation parameter space reservoir permeability neural network objective function interpolation algorithm assumption porosity permeability artificial neural network modeling dilation curve Introduction Due to the gradual depletion of conventional oil and gas reservoirs with high...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193848-MS
... it to be useful for engineers designing IOR pilot for brown fields with complex reservoir models. Artificial Intelligence objective function machine learning history matching reservoir simulation variance Effectiveness statistical model uncertainty reduction conditioning workflow joint...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193860-MS
... Index (HMQI) with Moving Linear Regression Analysis to evaluate simulation results from history matching process. The HMQI provides normalized values for all objective functions having different magnitude and leads to a more consistent and robust approach to evaluate the updated models through model...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193856-MS
... development activities by obtaining optimization solutions that are robust against changes in future decisions, and (2) considerably reduces the performance losses that can result from field development when uncertainty is disregarded. optimization problem objective function Artificial Intelligence...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193842-MS
... the objective functions. The study demonstrates the potential impacts of reservoir heterogeneities on the WSI process. Models with different heterogeneity settings are examined. The results reveal that the impacts of shale barriers may be more/less evident under different circumstances. The proxy models can...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193883-MS
... significant increases between 5% and 20% in the expected value of the objective function were achieved. For the multi-objective optimization cases we show that non-trivial optimal strategies are obtained which significantly reduce (40% decrease) gas production with minimal loss (less than 1%) in the economic...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193914-MS
... optimization under uncertainty is an iterative process that considers all history matched ensemble members. The goal in this step is to find a set of inputs that optimize an objective function derived from all ensemble outputs. Those outputs are computed scalar values such as NPV ( Sorek et al. 2017a , b...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193926-MS
... of the history match and the quality of the forecast. So, the traditional belief that a good history matched model will also produce a good forecast is not always true. Artificial Intelligence Upstream Oil & Gas correlation Modeling & Simulation objective function variation history matching...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193916-MS
... Intelligence training data Optimization Method gmm sample inverse covariance matrix error function gaussian component fitting method Gao normalized error function gmm fitting formulation formulation Upstream Oil & Gas objective function History algorithm uncertain parameter gmm fitting...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193923-MS
... objective function OPC base solution optimal solution Injection Rate candidate solution water production long-term opc Artificial Intelligence constraint optimization workflow Optimization Opportunity case study reservoir Scenario Introduction As volatility in oil prices is a new norm...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182602-MS
...-Newton trust region approach, which is applicable for large scale history matching problems with negligible extra cost in CPU and memory. optimization problem CPU time reservoir simulation objective function Artificial Intelligence Upstream Oil & Gas iteration computational cost...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182597-MS
... for optimization under uncertainty to real field cases. If CO 2 storage credits are added to the objective function, a different control strategy is found that also leads to an increase in NPV. This result highlights the potential for economic incentives to increase both CO 2 storage and oil recovery. We also...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182632-MS
...Proposed WLO workflow The workflow presented here is designed to assist subsurface specialists in exploring well configurations that maximize an objective function. The optimization starts with a feasible base case – a set of well locations that includes subsurface and engineering...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182598-MS
... technique with a gradient-based method for solving large-scale continuous problems that have thousands of variables. An adjoint method is used to compute efficiently the derivatives of objective functions with respect to decision variables and a sequential quadratic programming method is used...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182609-MS
... enhanced recovery machine learning Upstream Oil & Gas posterior uncertainty reservoir simulation variance information eva method assumption proxy uncertainty parameter Artificial Intelligence objective function uncertainty reduction multi-gaussian assumption realization pbpa...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182639-MS
... constraint RML method machine learning reservoir simulation objective function unconditional realization Artificial Intelligence history matching computational cost realization Reynolds base case global-dgn rml method production data algorithm green curve Bayesian Inference Upstream Oil...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182693-MS
... the solution. They can be categorized into two classes: Tikhonov regularization and iterative regularization ( Doicu, Trautmann, & Schreier, 2010 ). In Tikhonov regularization, the regularization term is added to the objective function directly which is then optimized. In iterative regularization...

Product(s) added to cart

Close Modal