The Benefits of Integrated Asset Modeling: Lesson Learned from Field Cases

Abstract

Nowadays oilfield development has become more technically and economically challenging and a high degree of interdisciplinary interaction is needed to have an effective and efficient management of the field. The achievement of this goal is made possible only if all the different resources of an organisation work together sharing the same reservoir model. Indeed, the main breakthrough behind Integrated Asset Modeling (IAM) is to combine reservoir, production and surface engineering modeling into an asset management tool that allows the simulation of the whole oilfield system. Though the need and the benefits of IAM were already recognised during the seventies, it is only in the last decade that software tools required to perform integrated production simulation have become available. Coupling dynamic reservoir and surface facility models into a single integrated model may address the following issues: pressure interaction between the surface and the subsurface; mixing of different fluids and flow assurance; accounting for facilities constraints; and identification of system bottlenecks and backpressures. In this way, unnecessary drilling can be avoided, new opportunities can be discovered, optimal artificial lift programs can be implemented to meet production targets. In this paper the state of the art of IAM tools is reviewed, with emphasis on the solution implemented in our company. Benefits and criticalities are then discussed on the basis of three cases, including integrated models for regional gas production systems, deep water mixed oil-gas assets and gas lifted reservoir. Indeed, it has been noted that integrated surface-subsurface modeling will have a critical impact on field management by offering increased accuracy in forecasting reservoir behaviour and maximising the recovery factor at minimum cost. Introduction During the last decade, oil companies attempted to reorganise their structures into interdisciplinary asset teams and include IAM in industry workflows. This was mainly due to an acknowledgement of the need for a better understanding and description of the interaction between subsurface-surface systems. It was facilitated by more powerful IT resources and commercial tools for IAM. Despite the availability of several commercial platforms, many major petroleum companies have implemented their own proprietary softwares over time. One of the pioneer solutions to IAM dates back to the 1960s when Amoco (Tingas et al., 1998) developed on a mainframe computer RAISEGAS (Mohamed et al., 1979), a single phase - 2D reservoir and surface network simulator, to manage the production of coupled Southern North Sea UK gas fields. Extension to two phase gas-water systems was presented by Dempsey in 1971 for gas field deliverability. It is with the works of Chevron (Startzman et al., 1977; Emanuel et al., 1981; Breaux et al., 1985) that IAM began to be applied to three dimensional black oil reservoirs. Startzman coupled a black oil simulator to an in-house surface model. To reduce execution time Emanuel moved the interface between the models to the wellhead and used look-up tables for wellbore pressure losses, whilst Breaux presented two applications of the methodology that combined cost-effective drilling and facility scheduling with balanced reservoir development. More recently Chevron tightly coupled its own 3D reservoir simulator CHEARS with the commercial network simulator PIPESOFT2 and presented an application for the development plan of the Gorgon field offshore Northwest Australia (Zapata et al., 2001). Arco (Stoisits et al., 1992) developed its own integrated simulator and presented a case study of gas lift optimisation for the Kuparuk river field on the Alaskan North Slope.

Production Optimization Considering Interaction between Reservoirs and Constrained Surface Facilities

“…In the assessment of some authors (Zapata et al, 2001;Rotondi et al, 2008), the explicit approach is quite flexible, however, the consistency between the network and the simulator computations should be checked because the IPR used by the simulator output is computed by solving the well equations with cells pressure and saturations at time t, while other variables, including well rates or pressures, are updated with the IPR holding at time t+∆t. This may induce discrepancy between reservoir bottom-hole and network bottom-hole when the wells are controlled by a controller program under a target fluid rate.…”

Influence of well management in the development of multiple reservoir sharing production facilities

“…Several recent methodologies [6][7][8] have tried to improve coupling reservoir models and production system models to simulate integrated solutions, representing fluid flow through the reservoir to the surface, more accurately.…”

Effect of reservoir and production system integration on field production strategy selection

“…Currently, more studies integrating reservoir and production systems in petroleum field production are needed to analyze the pressure interaction between reservoirs, wells, gathering networks, and surface facilities. Barroux et al (2000), Kosmala et al (2003), Rotondi et al (2008), and Cotrim et al (2011) demonstrated the necessity of integrated methodologies to couple simulators to improve production forecast reliability and quality. For instance, when the reservoir simulator fails to model the operational conditions of complex production systems, integration with the process simulator becomes even more consequential.…”