Abstract
Field development planning of gas condensate fields using numerical simulation has many aspects to consider that may lead to a significant impact on production optimization. An important aspect is to account for the effects of network constraints and process plant operating conditions through an integrated asset model. This model should honor proper representation of the fluid within the reservoir, through the wells and up to the network and facility.
Obaiyed is one of the biggest onshore gas field in Egypt, it is a highly heterogeneous gas condensate field located in the western desert of Egypt with more than 100 wells. Three initial condensate gas ratios are existing based on early PVT samples and production testing. The initial CGRs as follows;160, 115 and 42 STB/MMSCF. With continuous pressure depletion, the produced hydrocarbon composition stream changes, causing a deviation between the design parameters and the operating parameters of the equipment within the process plant, resulting in a decrease in the recovery of liquid condensate. Therefore, the facility engineers demand a dynamic update of a detailed composition stream to optimize the system and achieve greater economic value. The best way to obtain this compositional stream is by using a fully compositional integrated asset model.
Utilizing a fully compositional model in Obaiyed is challenging, computationally expensive, and impractical, especially during the history match of the reservoir numerical model.
In this paper, a case study for Obaiyed field is presented in which we used an alternative integrated asset modeling approach comprising a modified black-oil (MBO) that results in significant timesaving in the full-field reservoir simulation model. We then used a proper de-lumping scheme to convert the modified black oil tables into as many components as required by the surface network and process plant facility. The results of proposed approach are compared with a fully compositional approach for validity check. The results clearly identified the system bottlenecks. The model can be used to propose the best tie-in location of future wells in addition to providing first-pass flow assurance indications throughout the field's life and under different network configurations. The model enabled the facility engineers to keep the conditions of the surface facility within the optimized operating envelope throughout the field's lifetime.
Pipe Network Evaluation for "X" Field Production Optimization
