Abstract

While designing Deep Offshore fields developments, several decisions have to be made : defining the system architecture, selecting technologies, defining operating and maintenance policies, etc. The objective is to ensure production by mitigating risks while lowering costs and maximising profits.

However, risks are numerous (e.g. equipment failures or Flow Assurance issues) and strongly interact with each other thus making the behaviour of the production process quite complex. Hence, in order to make correct decisions, engineers need a tool able to :

  • integrate various risks, especially those arising from Flow Assurance issues,

  • simulate accurately the complex behaviour of the subsea production system all along the field lifecycle,

  • estimate the performances of the candidate designs in order to choose the best one.

This paper describes a risk management methodology based on the general framework provided by Dependability. After a hazard identification step, a model is built based on hybrid interpreted stochastic Petri nets which allow to model complex interactive systems and mix both discrete (e.g. equipment failures) and continuous (e.g. progressive degradations such as corrosion or deposits) aspects of the production process. The model provides fast computations of the availability and production availability of the system thus giving criteria for risk management.

The methodology was applied to a simplified representative subsea production system and allowed to quantify the influence of major risks in terms of economic consequences and optimize a maintenance policy.

Introduction

The oil industry, while facing a constant increase of the world energy demand and a decrease of the conventional oil reserves, is turning towards new technological oil reserves, especially deep and ultra deep offshore reserves.

Deep and ultra deep offshore environment is very harsh : high pressure, low temperature, difficulties of intervention for maintenance and repair, subsea layout spreading over several kilometers in order to produce satellite fields etc. Indeed, risks are very high while CAPEX rise up to several billions of dollars. In this context, several crucial decisions have to be made : defining the system architecture, selecting technologies (e.g. lines insulation technology), defining operational and maintenance policies etc. The objective is to ensure the maximum production at the lower cost, especially by mitigating in an economic way various risks such as equipment failures or Flow Assurance issues (hydrate plugging, wax deposition, etc.).

One of the main problems is the great complexity of the production process. Indeed, risks strongly interact with each other : as an example, equipment failures may stop the subsea production system and possibly lead to major Flow Assurance risks (like hydrate plugging) depending on shutdown duration. Therefore, engineers need special tools in order to simulate accurately the complex behaviour of the subsea production system all along the field lifecycle and give some measure of its performance. The main objective is to estimate, while designing the system, the impact of a given decision as a risk on the economy of the project.

It appeared quickly that Dependability defines a theoretical framework well suited to solve this type of problem.

This content is only available via PDF.
You can access this article if you purchase or spend a download.