This paper summarizes the results and learnings from the Autonomous Inflow Control Device (AICD) deployment and installation in multiple heavy oil fields in south Oman, allowing for swift utilization in other fields with similar characteristics. Those AICDs were mainly deployed and tested in those oil fields comprehensively, in horizontal producers, and the results were supported by rigorous lab tests was conducted to understand their behavior. This paper is a continuation of the work in reference [1]. In recent decades, horizontal drilling for producing wells became a widely known and used technology, this is due to the fact they improve the overall recovery, efficiency of production, drainage of the reservoir, as well as delay unwanted fluids (e.g. gas & water). However, this solution was not perfect, as due to highly fractured and heterogeneous reservoirs, premature water and gas production can and will take place, causing remaining oil to be bypassed, and hence, reducing the reservoir's recovery and eventually the profitability [2]. In south Sultanate of Oman, many fields have been developed with the use of the horizontal well technology, but together with its advantages, the geological nature of the formations and the physical properties of the produced fluids, have introduced important challenges regarding production optimization. One of the assets in question comprises of naturally fractured carbonate reservoirs drained through long horizontal open-hole completions. It has been developed with water flood and GOGD system. The main production optimization challenge faced for that asset is the fracture-dominated inflow, which leads to either high water or gas production. On the other hand, another asset where the trial took place comprises of shallow sandstone reservoirs of heavy oil, with strong bottom aquifers and high level of reservoir heterogeneities; fractures, faults and high permeability streaks are characteristic of these reservoirs. A horizontal well usually has a much higher capacity–as compared to a vertical well–for producing fluids at the same drawdown, hence, when talking on critical rates that do not disturb the oil-water-contact, horizontal wells will definitely have a higher critical rate than those of vertical wells, but even so, the capacity of moving fluids are bigger, causing faster movement of bottom water towards the horizontal well regardless [3]. Another field of the trial fields had produced heavy oil, with viscosities in the range of 600 cP to 1000 cP. The permeability is variable and in the range of 100mD to 10D. This makes the mobility ratio very favorable to water production. Some wells have started production with less than 10 % WC, but a sudden increase of WC has been observed up to above 90 %. Most of the wells have been completed with inflatable packers (EZIPs), creating 2 to 3 segments at the horizontal reservoir section. The AICD technology is suitable for being applied in this case of very low oil mobility and segments at the sand-face. The last trial field comprises of multi-stacked reservoirs, isolated by shale barriers, with production potential of oil from two main layers. The oil is light, ~ 42 API and 0.9 cp viscosity. Around 13 wells are closed-in due to various reasons including high water cut and low productivity. This field is producing since 1998 from 9 stacked reservoir zones-commingled, which provides a challenge to production allocation. Performing Production Logging Tests–PLTs-have not helped to improve the allocation issues. Water shut off is challenging when it comes to the point of deciding the zone required to be closed. Mechanical water shut off is an option to choke back the non-allocated water zones and allow more oil production. Although this field does not include horizontal wells, the total perforated length of the proposed well and the hydraulic natural isolation between the producing zones makes the application of the technology attractive for this field. An interventionless/wireless technology, which promotes uniform production along the entire length of a horizontal well, delaying the production of unwanted fluids (water or gas) from high productivity zones along the well path and promoting increased oil production from other compartments of the formation, would definitively represent a key aspect of the production optimization for these Petroleum Development Oman fields.
Recent developments in electrical power grids have witnessed high utilization levels of renewable energy sources (RESs) and increased trends that benefit the batteries of electric vehicles (EVs). However, modern electrical power grids cause increased concerns due to their continuously reduced inertia resulting from RES characteristics. Therefore, this paper proposes an improved fractional-order frequency controller with a design optimization methodology. The proposed controller is represented by two cascaded control loops using the one-plus-proportional derivative (1 + PD) in the outer loop and a fractional-order proportional integral derivative (FOPID) in the inner loop, which form the proposed improved 1 + PD/FOPID. The main superior performance characteristics of the proposed 1 + PD/FOPID fractional-order frequency controller over existing methods include a faster response time with minimized overshoot/undershoot peaks, an ability for mitigating both high- and low-frequency disturbances, and coordination of EV participation in regulating electrical power grid frequency. Moreover, simultaneous determination of the proposed fractional-order frequency controller parameters is proposed using the recent manta ray foraging optimization (MRFO) algorithm. Performance comparisons of the proposed 1 + PD/FOPID fractional-order frequency controller with existing PID, FOPID, and PD/FOPID controllers are presented in the paper. The results show an improved response, and the disturbance mitigation is also obtained using the proposed MRFO-based 1 + PD/FOPID control and design optimization methodology.
This article proposes a hybrid scheme of maximum power point tracking (MPPT) based on artificial neural network (ANN) and ripple current correlation (RCC). ANN model is established using the data generated through RCC MPPT. Scaled conjugate gradient ANN is applied to gauge the performance improvement. The proposed scheme is validated through simulations. For this, the proposed system is applied to three different environmental scenarios which are standard testing condition of a PV module, under variable irradiance condition, and variable temperature condition. It is established that the proposed system is well capable of tracking the maximum power point under various test conditions.
Several techniques have been applied to improve fluid conformance of injection wells to increase water flooding performance and eventually field oil recovery. Normal outflow control devices (OCDs) are effective solutions for this problem in reservoirs with static properties, however, they fail in reservoirs with complex/dynamic properties including fractures. There, the continuously increasing contrast in the injectivity of a section with the fractures compared to the rest of the well causes diverting a great portion of the injected fluid into the thief zone thus creating short-circuit to the nearby producer wells. This paper summarizes the integrated technical learnings from the successful application of the installation of the first Autonomous Outflow Control (AOCD) technology in a new long horizontal injector well. It shows the result of extending this technology to other injectors in both water and polymer phases in the field, it details the facts and observations and the insights the multidisciplinary authors have captured. This autonomously reactive control on the injection fluid conformance resulted in an increased sweep and ultimate oil recovery while reducing the total volume of injected fluid.
With limited and scarce subsurface and surface data, it becomes quite challenging to monitor a rather large field, having more than 50 wells actively producing, and actively optimize the production, achieving the desired production rates and maximizing the benefit for the operator and partners. The field in question was inherited from the previous operator, with 27 legacy wells, and a surface facility capable of processing ca. 100kbb/d of crude. Additional processing facility was installed to double the legacy capacity and 30 wells drilled by the time of preparing this paper for supplying the crude. The field had a shut-in period of 14 months in 2011-12 for various upgrades and surface works. It was then necessary to introduce an integrated modelling tool, to allow for a more efficient control and monitoring of the producing asset, combining all the components together and testing the interactions between the different system parts. The Integrated Production System Model (IPSM) was built based on the principle of following the oil molecule from the pore throat to the export. As such, it comprises of three main components, linking the subsurface to the surface, those are: –Reservoir Models (built with Petex® MBAL©)–Well Models (built with Petex® PROSPER©)–Trunklines/Flowlines and Separators (built with Petex® GAP©) Petroleum Experts® (Petex) develop the Integrated Production modelling software suite that comprises the tools mentioned above and are the company's proprietary. The current version of the IPSM is used in variety of situations; these include mainly but not limited to: ▪Medium Term Production Forecasting (MTPF)▪Production System Optimization (PSO)▪Opportunities assessment▪Identification of bottlenecks▪Further well scoping The IPSM has facilitated the application of many processes, allowing for a faster and more informed decision making, these include: ▪Optimization: as required and identified in PSO Meetings, optimization activities are carried out as part of increasing the total system production output, which adds more value to this process▪MTPF: generated on a monthly basis, the MTPF clearly highlights the production pitfalls, and the expected targets with a given set of assumption, and honouring the constraints that exist in the system, allowing for proper future planning, and the need for well scoping studies and highlight of the requirements to meet the desirable targets▪Maturing opportunities and assessing their system gains and impact on system This paper presents the process of building and maintaining an IPSM model throughout the different phases of a super giant field's life, from early production days with limited wells and data to the point of having real time data transferred to the office, fully utilizing the available data help make decisions that maximizes and eliminates waste.
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