Prediction of Souring in Infill Wells using Standalone Extended 2D Simulator for a Malaysian Offshore Field

摘要

Hydrogen sulfide (H2S) production in a sea water injected, high temperature offshore reservoir is causing concern, because the existing wells and facilities are not designed for sour service. This is challenging for the design and material selection for two upcoming infill opportunities in this reservoir, which will be dictated by the reservoir souring predictions. The reservoir under consideration is one of the major reservoirs in a prominent Malaysian offshore brown field area. The reservoir commenced production in 2002 closely followed by the start of sea water injection. Injection of the sulphate containing sea water has been known to trigger H2S production because of the activity of sulphate reducing bacteria (SRB). Understanding the need for modeling H2S generation and propagation, PETRONAS and Heriot-Watt University have jointly developed a simple standalone extended 2D reservoir souring simulator, referred to as a 2D+ Souring Model. The 2D+ Souring Model considers two phase flow (oil and water) in the porous medium (rock formation) based on the normal multiphase flow equations. The full reservoir flows are simulated by building "panels" to connect all of the corresponding injectors and producers. Each panel is a layered cross-sectional model with different permeability layers. The geo-thermal considerations are based on heat transfer due to convection and conduction. The simulator considers bacterial growth both in planktonic and sessile forms. Monod microbial kinetics is applied for the growth of SRB and NRB, leading to the consumption of sulphate/nitrate and substrate (volatile fatty acids) which in-turn is linked to H2S generation. Along with H2S propagation, H2S scavenging by rock and H2S partitioning between the various phases is also accounted for. This paper explains the souring simulation and H2S, oil and water production history matching conducted for the reservoir. For infill wells souring prognosis, the model is run based on parameters obtained from history matching. It provided reasonable souring predictions which have been used for the infill well material specification and design.