A multiperiod planning model for gas production system

Flores-Salazar, M.A.; Vázquez-Román, Richart; Grossmann, Ignacio E.; Iglesias‐Silva, Gustavo A.

doi:10.1016/j.petrol.2011.03.007

Cited by 10 publications

(8 citation statements)

References 45 publications

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“…The well produces oil with a constant volumetric flow rate q i up along the entire operation time t i o . According to Flores-Salazar et al 30 the production in each time period must be at constant rate to avoid the "heading" in wells. If the well has been closed long enough, it is assumed that P i in is equal to the reservoir pressure.…”

Section: Problem Backgroundmentioning

confidence: 99%

Disjunctive Optimization Model for the Production Planning and Blending of Crude Oil in a Conventional Oil Field

Duckwen

Moreno

Borio

et al. 2018

Ind. Eng. Chem. Res.

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This work presents a multiperiod nonlinear formulation based on generalized disjunctive programming (GDP) that integrates the production planning and pooling problems in a conventional onshore oil reservoir with fixed topology and a surface interconnection scheme. The model optimizes the well production and blending decisions, while complying with product specifications, such as the sulfur content required by refineries downstream of the oil field. It considers wells from different reservoirs belonging to a given oil field, which are interconnected through manifolds at a network of pipes. The nonlinear behavior of well pressure as a function of time and bilinearities in mass balances are also taken into account. The objective function maximizes the accumulated production of the end products. Numerical results show that obtaining end products as result of blending operations is affected by production planning in wells, the capacity of intermediate tanks, and sulfur specification.

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Section: Problem Backgroundmentioning

confidence: 99%

Disjunctive Optimization Model for the Production Planning and Blending of Crude Oil in a Conventional Oil Field

Duckwen

Moreno

Borio

et al. 2018

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

show abstract

“…Equation 14 forces the molar flow rates of streams exiting the splitter to be zero when the corresponding process shuts off. Equation 15 represents the mass balance for individual chemical components in the splitter. Equation 16 expresses the sum of all the mole fractions of a stream exiting processes.…”

Section: Splittersmentioning

confidence: 99%

“…The uncertainty related with product quality in the proposed natural gas production network was addressed later by Li et al 13 Tabkhi et al 14 investigated the models of pipelines and compressors for long distance transportation of gas, and used these models to minimize fuel consumption in the compression station. Flores-Salazar et al 15 presented a multiperiod mathematical model for gas and oil production systems on the basis of two conceptual process units (well and manifold). The total production cost is simplified as a result of a cost coefficient multiplied by the capacity of well.…”

Section: Introductionmentioning

confidence: 99%

Operational strategy and planning for raw natural gas refining complexes: Process modeling and global optimization

Zhang

Chen

et al. 2016

AIChE Journal

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Optimal operational strategy and planning of a raw natural gas refining complex (RNGRC) is very challenging since it involves highly nonlinear processes, complex thermodynamics, blending, and utility systems. In this paper, we first propose a superstructure integrating a utility system for the RNGRC, involving multiple gas feedstocks and different product specifications. Then, we develop a large-scale nonconvex mixed-integer nonlinear programming (MINLP) optimization model. The This article is protected by copyright. All rights reserved. Finally, the reformulated nonconvex MINLP model is solved to global optimality using state of the art deterministic global optimization approaches. The computational results demonstrate that a significant profit increase is achieved using the proposed approach compared to that from the real operation.

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“…However, the second group uses the mathematical programming technique. − An example is a series of studies by Tavallali, Karimi, and their co-workers; they tackled the static and later the dynamic well placement problem , and formulated these problems through a framework for mixed integer nonlinear programming (MINLP) problems. Their model included rigorous reservoir dynamics, as well as many logical decisions implemented in GAMS optimization package.…”

Section: Introductionmentioning

confidence: 99%

Optimal Drilling Planning by Considering the Subsurface Dynamics—Combing the Flexibilities of Modeling and a Reservoir Simulator

Tavallali

Bakhtazma

Meymandpour

et al. 2018

Ind. Eng. Chem. Res.

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Many drilling and oil companies are facing tight budgets, and a promising option for survival is to optimally revisit the drilling plans and production operations. Although there are some options for this task in the current reservoir simulators, more in-depth analysis is indeed required. Hence, in this study we borrow the flexibilities and capabilities of both modeling and a reservoir simulator to spatiotemporally plan the drillings of new injector and/or producer wells, determine the total number of new wells, and schedule the production/injection from all wells. The entire approach is both mathematically enriched and simple to use in the industry. We show that our methodology outperforms the decisions of an industrially accepted reservoir simulator in two separate examples by 4.4% and 2.4%, respectively.

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A multiperiod planning model for gas production system

Cited by 10 publications

References 45 publications

Disjunctive Optimization Model for the Production Planning and Blending of Crude Oil in a Conventional Oil Field

Disjunctive Optimization Model for the Production Planning and Blending of Crude Oil in a Conventional Oil Field

Operational strategy and planning for raw natural gas refining complexes: Process modeling and global optimization

Optimal Drilling Planning by Considering the Subsurface Dynamics—Combing the Flexibilities of Modeling and a Reservoir Simulator

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