The paper discusses the pilot project in ADNOC Offshore to assess the Autonomous Inflow Control Device (AICD) technology as an effective solution for increasing oil production over the life of the field. High rate of water and gas production in horizontal wells is one of the key problems from the commencement of operation due to the high cost of produced water and gas treatment including several other factors. Early Gas breakthrough in wells can result in shut-in to conserve reservoir energy and to meet the set GOR guidelines. The pilot well was shut-in due to high GOR resulted from the gas breakthrough. A pilot project was implemented to evaluate the ability of autonomous inflow control technology to manage gas break through early in the life of the well spanned across horizontal wellbore. And also to balance the production influx profile across the entire lateral length and to compensate for the permeability variation and therefore the productivity of each zone. Each compartment in the pilot well was equipped with AICD Screens and Swell-able Packers across horizontal open hole wellbore to evaluate oil production and defer gas breakthrough. Some AICDs were equipped with treatment valve for the compartments that needed acid simulation to enhance the effectiveness of the zone. The selection factors for installing number of production valves in the pilot well per each AICD was based on reservoir and field data. Pre-modeling of the horizontal wellbore section with AICD was performed using commercial simulation software (NETool). After the first pilot was completed, a detailed technical analysis was conducted and based on the early production results from the pilot well showed that AICD completions effectively managed gas production by delaying the gas break through and restricting gas inflow from the reservoir with significant GOR reduction ±40% compared to baseline production performance data from the open hole without AICD thus increasing oil production. The pilot well performed positively to the AICD completion allowing to produce healthy oil and meeting the guidelines. The early production results are in line with NETool simulation modelling, thereby increasing assurance in the methods employed in designing the AICD completion for the well and candidate selection. This paper discusses the successful AICD completion installation and production operation in pilot well in ADNOC Offshore to manage GOR and produced the well with healthy oil under the set guidelines. This will enable to re-activate wells shut-in due to GOR constraint to help meeting the sustainable field production target.

Wells 1A, 2A, 3A & 4A are designed as four (4) horizontal oil producers to maximize the oil recovery from the XXYY heterogenous sandstone reservoir in Offshore Malaysia. The reservoir has been producing since 1975 on natural depletion before gas injection (1994) and water injection (2019-2022) were introduced. XXYY reservoir is expected to have wide permeabilities ranges from as low as 1-mD to 4-D and high uncertainty of gas-oil contacts from recent saturation logging acquisition. Coupled with the complex reservoir nature of massive gas cap and thinning oil rim observed between 30-50ft-TVD, historical production of oil with optimum GOR in XXYY reservoir remained the main challenge towards late field life. For such challenging condition, pre-planning with multiple Autonomous Inflow Control Device (AICD) valve placement scenarios across the horizontal sections were analyzed using integration of reservoir and well models for valves optimization process to achieve well's target production and reserves by the end of PSC. Specific drawdown and production targets were set as critical design limits in managing sanding and erosional risks while still achieving production target. Ultimately, these models provided both instantaneous and long-term forecasts of AICD impact on the wells’ performance – key factors in the final design. The workflow presented in this project synergized scope of multi-domain from subsurface, completion and drilling. This case study demonstrates the value of detailed design steps on AICD placement across horizontal segments and optimizations based on actual open-hole logging interpretation, mainly – permeability, saturation and vertical stand-offs from gas-oil and oil-water contacts. The horizontal wells drilled are susceptible to "heel-toe" effect, resulting in dominant production in the heel section while the toe section contributes less, subsequently inducing gas coning at the heel. XXYY reservoir is also sand prone and requires sand control. For these reasons, all 4 wells are designed to be completed with Open Hole Stand Alone Screen (OHSAS) with the use of AICD to balance production withdrawal across the horizontal segments and provide GOR control. The four (4) wells penetrated 30-60ft-TVD of oil column with 10-15ft-TVD vertical stand-offs from gas-oil contact (GOC) to maintain a 2/3 column ratio from oil-water contact. Given these marginal stand-offs to GOC, integration of AICD sensitivities workflow were performed on-the-fly to analyze instantaneous and time-stepped oil and GOR rates allowing the team to achieve required production sustenance. The installations of optimized AICD have resulted in successful GOR control below 6 Mscf/stb targeted, resulting in delivering higher instantaneous production rates against planned of 4,600bopd. The success of AICD optimizations integrated with OHSAS completion, reservoir mapping and petrophysical evaluation have been proven as ultimate solution to deliver the wells oil production for a brown field rejuvenation project. The pre-drill and post-drill results calibrated to actual well tests are compared for further sensitivity analysis, to be used in the continuous improvement of production management strategies in the field.

Inflow Control Device (ICD) completions can improve well performance by adjusting the inflow profile along the well and reducing the influx of unwanted fluids. The ultimate aim of using ICD completions is to provide maximum oil recovery and/or Net Present Value (NPV) over the life of the field. Proactive ICD optimisation studies use complex reservoir models and high-dimensional nonlinear objective functions to find the optimum ICD configurations over the life of the field. These complex models are generated from fine scale detailed geological models to accurately capture fluid flow behaviour in the reservoir. Although these high-resolution geological models can provide better performance predictions, their simulation runtimes can be computationally expensive and time consuming for performing proactive ICD optimisation studies that often require thousands of simulation runs. We propose a new workflow where we use upscaled and locally refined models coupled with parallelised global search optimisation techniques to improve the simulation efficiency when performing ICD optimisation and decision-making studies. Our approach preserves the flow behaviour in the reservoir and maintains the interaction between the reservoir and the well in the near wellbore region. Moreover, when coupled with parallel optimisation techniques, the simulation time is significantly reduced. We present an in-house code that couples global search optimisation algorithms (Genetic Algorithm and Surrogate Algorithm) with a commercial reservoir simulator to drive the ICD configurations. We evaluate the NPV as the objective function to determine the optimum ICD configurations. We apply and benchmark our approach to two different reservoir models to compare and analyse its efficiency and the optimisation results. Our analysis shows that our proposed approach reduces the run time by more than 80% when using the upscaled models and the parallel optimisation techniques. These results were based on a standard dual-core parallel desktop configuration. Additional results also showed further reduction in run time is possible when employing more processors. Additionally, when testing different ICD completion strategies (ICDs in producers only, ICDs in injectors only, and ICDs in both producers and injectors), the NPV can be increased by 9.6% for the optimised ICD completions. The novelty of our work is rooted in the much-improved simulation efficiency and better performance predictions that supports ICD optimisation and decision-making studies during field development planning to maximize profit and minimize risk over the life of the field.

Inflow control device (ICD) completions are becoming a crucial part for many green and brown field developments. However, a typical ICD completion requires a washpipe or inner string to provide fluid circulation, displacement and setting of openhole hydraulic-mechanical packers, which increases operational time, risks and costs. A typical installation process has to follow a series of operational steps to ensure successful deployment of ICD completions. Those necessary operational steps are traditionally achieved using washpipe or an inner string that is run inside the lower completion bottomhole assembly (BHA). This unique and advanced ICD completion design uses proven sliding-sleeve technology that will be run in the closed position to provide fluid circulation, displacement and setting of openhole hydraulic -mechanical packers, and then hydraulically activated to the open position to allow for reservoir-to-well communication. It also incorporates a mechanical-shifting mechanism for future reservoir management and control. The new and advanced ICD completion has undergone a rigorous testing program to ensure the design will deliver those operational requirements and perform appropriately under the worst well operational conditions that are expected during the field life. Following completion of the testing program, the advanced ICD completion was deployed flawlessly in a carbonate reservoir well in the Middle East, representing the first successful deployment globally. The system has functioned as expected with clear surface indication throughout the different operational steps and the final establishment of reservoir-to-well communication which was evidenced by the increase in the well head pressure (WHP). Furthermore, the individual ICD open or closed-sleeve status was verified through production logging (PLT) and coil tubing (CT) shifting operations. The paper describes a comprehensive qualification testing program for the advanced ICD completion design to best serve those well-installation requirements without the need of washpipe. Furthermore, it details the actual well deployment which resulted in improved overall well completion design and operational efficiency.

Advanced or smart completion wells are different from conventional wells by being equipped with downhole flow control devices such as Interval Control Valves (ICV) and Inflow Control Devices (ICD) to offer improved reservoir management and control and thus maximise hydrocarbon production and recovery. In order to justify their implementation and increase their economic return, a high degree of robustness in modelling, prediction and optimisation of their performance is required. To improve the robustness of forecasting production from advanced or smart wells using reservoir simulation, high-level details in rock and fluid flow properties are needed in the near-wellbore region to accurately capture the flow dynamics. The paper presents an improved approach that enables us to robustly predict the performance of advanced or smart wells in reservoir simulation and highlights the importance of representing the near-wellbore region when optimizing smart well completions. Performances of advanced or smart well completions are very dependent on changes in flow rate, pressure, and saturations, which mainly occur in areas around the wells. The paper demonstrates the use of local grid refinement (LGR) in the near-wellbore region to enhance the accuracy level of simulation predictions. In the study, an objective function based ICV optimization strategy was used to identify the optimum settings for every time step during the simulation run. We also demonstrate how to correlate ICV settings to Passive Inflow Control Device (PICD) or Autonomous Inflow Control Device (AICD) strengths if a requirement arises to impose the use of ICVs. Using a well-established synthetic reservoir model, we demonstrate how the representation of the near-wellbore region impacts reservoir performance predictions and influences the way ICVs and ICDs are optimized. We observe that by applying this approach, the predicted NPV and recovery factor change by 6.6% and 6.1%, respectively. In addition, this study also quantifies the impact of near-wellbore representation on four completion types; Openhole, ICV, PICD and AICD completions. The novelty of this paper is that it presents an approach to improve production forecasts that supports decision making during field development planning to maximize profit and minimize risk.