Inflow control devices (ICD) completion is a downhole flow control solution that is designed to balance influx contributions across wellbore horizontal section, to delay water breakthrough or coning hot-spots and to increase ultimate cumulative oil recovery. This paper illustrates a novel and successful systematic workflow to implement this technology in order to effectively manage the marginal green reservoir uncertainties while achieving field development requirements. In general, this production-upsides justification and design process started from an early stage full field ICD completion feasibility study; followed by single well pre-drill ICD design through dynamic simulation as preparation for real time drilling operation support. Subsequently, ICD nozzle-configuration optimization and packer placement design fine-tuning were performed before run in hole during real time operation. The final optimized design for ICD and tracer tally can then be proposed for on-site execution. The key enabler of this process is a novel and time-efficient single well dynamic simulation method, which is compiling the dynamic time-lapse production responds with various ICD nozzle and packer design optimisation workflow. The sensitivities of various design scenarios were applied as a working range to guide on-site ICD installation.

This paper highlight the design and optimization workflow from the perspective of dynamic modeling against the conventional nodal-based or single time-step production scenario simulation carried out. In illustrating the more ‘down-to-earth’ production upside results when time-lapse impact are considered, single well dynamic modeling can provide a more realistic real-time design especially in marginal oilfield application and critical decision-making during real-time. Against the typical over-optimistic production upsides analysis result portrayed by conventional single time-step production scenario simulation, some actual design cases as conservatively predicted by dynamic modeling single well will be demonstrated to influence decision-making when ICD's upsides is marginal . This crucial differentiation in due dilligence upside analysis will guide towards most optimal ICD's configuration RIH or reciprocally applying standalone screen (SAS) instead against the ICD's RIH minimal production benefits against its cost value. The results showed that the uncertainties and production repercussion that are affecting the decision of either running ICD's or SAS during real-time ICD's modeling updates are handled more inclusively and objectively with time-lapse based dynamic prediction.

You can access this article if you purchase or spend a download.