Model-Based Integration and Optimization – Gas Cycling Benchmark

Abstract

A benchmark for computational integration of petroleum operations has been constructed. The benchmark consists of two gascondensate reservoirs producing to a common process facility. A fraction of the processed gas is distributed between the two reservoirs for gas injection. Total project economics are calculated from the produced streams and process related costs. This benchmark may be used to compare different computational integration frameworks, and optimization strategies.The methods of model integration and optimization discussed in this paper are applicable to complex petroleum operations where it is difficult to quantify cause-and-effect without comprehensive model-based integration. A framework for integration of models describing petroleum operations has been developed. An example test problem is described and studied in detail. Substantial gains in full-field development may be achieved by optimizing over the entire production system.All models and data in the benchmark problem are made available so that different software platforms can study the effects of alternative integration methods and optimization solver strategy. The project itself can, and probably should, be extended by others to add more complexity (realism) to the reservoir, process, and economics modeling.

Process control in conventional oil and gas fields—Challenges and opportunities

“…There are, however, benefits to be gained. A realistic benchmark of a tightly coupled system has recently been introduced as a means to compare integration options in terms of costs and benefits (Juell, Whitson, & Hoda, 2009;Rahmawati, Whitson, Foss, & Kuntadi, 2010). Such a benchmark may provide a credible reference for comparing alternative solutions, in particular the potential gain of integrating reservoir and process utilities into one optimization application.…”

Multi-Field Asset Integrated Optimization Benchmark

“…The surface facility model is a steady-state model while the reservoirs are modeled using dynamic models to account for depletion effects. The model is an extension of the full-field model from a previous paper [Juell, et al, 2009].…”

“…The reservoir models include two gas-condensate reservoirs and an oil reservoir. The gas-condensate reservoirs are scaled up from [Juell, et al, 2009] and the oil reservoir is a scaled up version of a miscible WAG project [Killough and Kossack, 1987]. In the base case each reservoir is producing through 5 production wells and injection operations are conducted through 8 injection wells which perform gas injection wells in the gas-condensate reservoirs and WAG injection in the oil reservoir.…”

“…The composition for the gas-condensate reservoirs consist of 9 components and the composition for the oil reservoir consists of 6 components. The initial fluid composition for the gas-condensate reservoirs are referred to [Juell, et al, 2009] and for the oil reservoir is presented in Table 7 to Table 9. The compositional reservoir models are run using the SENSOR ® reservoir simulator.…”

“…Pipe-It ® is used as the integration platform for the I-OPT model meaning that it integrates and schedules the different applications for a given project run. This is similar to the solution in [Juell et al, 2009]. The I-OPT model is run by linking all software applications that transfer data from one application to another providing dynamic communication between the reservoir-well-manifold-pipeline and surface process facility simulators.…”