1-20 of 83
Keywords: objective function
Close
Follow your search
Access your saved searches in your account

Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, March 25–27, 2025
Paper Number: SPE-223837-MS
... simulator commercial simulator commercial reservoir simulator objective function forward simulation implementation Introduction Abstract Efficient history matching of reservoir simulation models remains a paramount challenge in the oil and gas industry, as it is crucial for improving...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, March 25–27, 2025
Paper Number: SPE-223850-MS
... ) , where J ( u ) is the objective function, i.e. the performance metric quantifying the quality of solutions in terms of the goals of the optimization, and u is the control vector containing the optimization or control variables describing the solutions, i.e. the degrees of freedom that may be varied...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, March 25–27, 2025
Paper Number: SPE-223866-MS
... Similarly to the previous works mentioned above, we employ a superposition principle and an optimization-based approach to compute a consistent stress field that honors the given measurements and equilibrium. We pose the compatibility problem by minimizing an objective function in the classical...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203950-MS
... matrix adaptation evolution strategy (CMA-ES). Results show that IBO achieves competitive objective function value with over 60% less number of forward model evaluations. Furthermore, the Bayesian framework that BO builds upon allows uncertainty quantification and naturally extends to optimization under...
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 enhanced recovery Upstream Oil & Gas reservoir simulation posterior distribution machine learning history matching Effectiveness uncertainty reduction...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193811-MS
... provides a good match with production data. flow in porous media Artificial Intelligence machine learning Fluid Dynamics modeling training data compaction-dilation data Upstream Oil & Gas interpolation neural network parameter space objective function algorithm society of petroleum...
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 asset and portfolio...
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-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-193923-MS
... by "twiddling the knobs" of software, as humans can be very good at comparing examples but unable to produce an optimal objective function ( Shahriari et al. , 2016 ). Third, an optimization opportunity never comes from nowhere. Understanding of its backing mechanism (e.g., physics) is the key to convince...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193914-MS
.... Like in history matching, production 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...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193916-MS
... & Gas error function gaussian component Gao fitting method normalized error function gmm fitting formulation formulation History algorithm uncertain parameter reservoir simulation training data Optimization Method gmm sample objective function gmm fitting method reduced-dof gmm fitting...
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 reservoir simulation case...

Product(s) added to cart

Close Modal