Inflow Control Valves Research Articles

Toward production zonal flow allocation using novel completion tracer dosing line and diffuser: Prototype laboratory flow loop experiments and computational fluid dynamics studies

Complex completion schemes with inflow control valves (ICVs) in multi-lateral wells are now the industry standard for modern fields. Understanding the production contributions from different production zones/laterals is of great importance in optimizing the zonal flow rates to prolong the field lifetimes, reduce water cuts and the associated costs, and achieve production targets. Furthermore, the improved operational efficiency can reduce the producers’ energy usages and carbon footprints for a more sustainable operation. For the past decade, inflow tracer technology based on embedding tracers in degradable polymer matrices, which are then placed in downhole completion zones at initial installation, has been used in understanding production zonal flow contributions in field demonstrations as well as in commercial projects. However, the current technology based on degradable polymers has the following limitations: (1) there are limited lifetimes for the degradable polymer matrices that will lose their functionality past their expiration dates, and (2) the tracers are released from the polymer matrices at a constant rate; so in order to create a transient for tracer flowback measurements the wells need to be shut-in for a period of time which will interfere with normal production and possibly, with the long-term productivity of the well. Here, we introduce an alternative approach for deploying inflow tracers that has no such limitations mentioned above. Specifically, we propose the installation of passive chemical tracer dosing lines connected to diffuser chambers at the annular regions downhole during completion. Pulses of tracers can be injected into the different production zones and monitored for their flowback characteristics on-demand. The passive tracer dosing lines and diffusers only require minimum upfront investments and have no limitations of lifetime compared to the degradable polymer matrices. Furthermore, the injection of tracer pulses into the annulus near production zones creates appropriate transient responses for their flowback measurements, which do not require well shut-in and will not affect normal production.Laboratory flow loop experiments and computational fluid dynamics (CFD) studies were performed to demonstrate the proposed methodology and to understand the underlying physics. Half-scale and quarter-scale flow loops made of transparent polyvinyl chloride (PVC) pipes that resemble annular regions near the ICVs were constructed with tracer dosing lines and diffusers attached within. Colored dyes were injected into the flow loops to visualize their flush out and flowback behaviors. In CFD studies, a two-step approach was used with first solving for the turbulent fluid flow profiles, and then solving for the tracer convection diffusion behaviors in the turbulent fields. The CFD model parameters were carefully matched with flow loop experiments to predict the possible real field responses. With appropriate diffuser design, we can achieve desirable zonal flow-rate-dependent tracer flowback responses with reasonable sampling times and injected tracer quantities.

Autonomous Inflow Control Valves Enable Better Water Control in Peru Oil Field

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 218074, “Making Better Wells With Autonomous Inflow Control Valves for Water Control in the Flank of the Bretaña Norte Oil Field, Peru: A Case Study,” by Willy Garcia, SPE, J. Antonio Zegarra, SPE, and Edwar Bustamante, PetroTal Peru, et al. The paper has not been peer reviewed. _ Bretaña Norte is a heavy oil greenfield in a remote area of northeast Peru. The field development strategy was designed around horizontal wells and advanced completions with autonomous inflow control devices (AICDs). As a part of a technology evaluation program, autonomous inflow-control-valve (AICV) technology was selected for field trials because of its ability to autonomously shut off water based on fluid properties. A reservoir simulation study was conducted, and the expected performance of AICV was compared with other AICD technologies installed in the field, indicating potential benefits related to better reservoir management. Field Description Bretaña Norte is an onshore field in the Peruvian Amazon. The Vivian formation is the main reservoir of the Bretaña Norte field and consists entirely of fluvial deposits composed of massive, moderately sorted, fluvial sandstones with thicknesses ranging from 40 to 200 ft. The Vivian formation is subdivided into Vivian S1 and Vivian S2, but only the Vivian S2 formation has been exploited to date. Heavy oil is produced from the Vivian S2 formation (18–19 °API and 25 cp), which features reservoir permeability ranging from 1 to 4 darcies. An active bottom aquifer of greater than 400-ft thickness was encountered under the60-ft oil column of the reservoir, posing a difficult production challenge to the operator: how to handle high volumes of water production that must be reinjected into a different formation. The Bretaña Norte field began production in 2018 with a few initial deviated wells with electrical submersible pumps (ESPs). The first horizontal well completed with standalone screens (SAS) experienced early water breakthrough. Thus, the operator opted for advanced completions with screens and AICDs in 2019. Between 2019 and 2023, 11 wells were completed with different AICD technologies. Even though initial results were positive, such outcomes have been highly dependent on the structural position of the wells. In 2022, a trial well was completed with the AICV technology in the flank of the reservoir, significantly closer to the oil/water contact (OWC), to evaluate its performance under challenging conditions. AICV Technology The AICV is an AICD designed to modify its open-flow area according to the properties (viscosity and density) of the fluids flowing through it and to choke flow progressively as water cut or gas-volume fraction values increase. The AICV is fully reversible, meaning that, if changes in the fluids flowing through the valve occur, it will reopen or reclose accordingly. The AICV consists of two flow paths, the main flow path and the pilot flow path, with an approximate flow distribution of 97 and 3%, respectively. Fig. 1 presents a schematic of the AICV, including a heat map showing the pressure distribution across the different flow paths.

The Current Status and Development Trend of Water Control Technology for Horizontal Wells

In the advancement of bottom water reservoir development, water breakthrough poses a significant challenge to the productivity of oil and gas wells, underscoring the paramount importance of effective water control strategies. Given the intricate nature of the factors leading to reservoir water breakthrough, a one-size-fits-all approach to water management is non-existent. Rather, tailored water control techniques are necessary to address the diverse causes of this phenomenon. This paper delves into the evolution and application of water control technologies, particularly focusing on the prevalent horizontal well water control methodologies. Horizontal well variable density water control, segmented water control, double horizontal well oil recovery water control, along with advanced solutions such as ICD (Inflow Control Device), ICV (Inflow Control Valve), AICD (Autonomous Inflow Control Device), and AICV (Autonomous Inflow Control Valve) water control systems are comprehensively introduced. Furthermore, center-controlled, mechanical plugging, and chemical plugging water control technologies are also examined in depth, accompanied by a thorough analysis of their respective strengths, limitations, and adaptability to various scenarios. By keeping abreast of both domestic and international trends in horizontal well water control, the future trajectory of this field is forecasted. Emerging as key technologies are novel composite water control systems, dual-purpose water control and sand prevention techniques, and intelligent water control solutions. These advancements promise to revolutionize the management of water breakthrough in bottom water reservoirs, enhancing oil and gas recovery efficiency and sustainability.

Comparative study on the optimal control of smart well in oil reservoir waterflooding with uncertainty

ABSTRACT In oil reservoir setting, an alternative for conventional wells are the smart wells having inflow control valves (ICVs). In this work, optimal control theory is implemented to investigate the performance of smart wells alongside conventional wells on an oil reservoir with permeability uncertainty and model mismatch. The performance of this scenario was compared using the Net Present Value (NPV) and Injection rates of the injector wells as perfromance indicators. The results obtained showed a better performance with smart wells irrespective of uncertainty and mismatch in the reservoir. An NPV of $4193430 was recorded for the smart well case as against its corresponding counterpart having an NPV of $3901415. Whereas for the faulted reservoir, an NPV of $314946 was obtained which is an 11% gain against the conventional well setting. This study shows that even though the rationale behind the implementation of conventional wells stems from their simple drilling process, they possess inherent limitation of sub-optimal reservoir-well contact depleting their productivity. Conversely, smart wells were shown to be better due to their enhanced monitoring and control capabilities making them suitable for reservoirs with uncertainties.

Derivative-free search approaches for optimization of well inflow control valves and controls

Decisions regarding problem conceptualization, search approach, and how best to parametrize optimization methods for practical application are key to successful implementation of optimization approaches within georesources field development projects. This work provides decision support regarding the application of derivative-free search approaches for concurrent optimization of inflow control valves (ICVs) and well controls. A set of state-of-the-art approaches possessing different search features is implemented over two reference cases, and their performance, resource requirements, and specific method configurations are compared across multiple problem formulations for completion design. In this study, problem formulations to optimize completion design comprise fixed ICVs and piecewise-constant well controls. The design is optimized by several derivative-free methodologies relying on parallel pattern-search (tAPPS), population-based stochastic sampling (tPSO) and trust-region interpolation-based models (tDFTR). These methodologies are tested on a heterogeneous two-dimensional case and on a realistic case based on a section of the Olympus benchmark model. Three problem formulations are applied in both cases, i.e., one formulation optimizes ICV settings only, while two joint configurations also treat producer and injector controls as variables. Various method parametrizations across the range of cases and problem formulations exploit the different search features to improve convergence, achieve final objectives and infer response surface features. The scope of this particular study treats only deterministic problem formulations. Results outline performance trade-offs between parallelizable algorithms (tAPPS, tPSO) with high total runtime search efficiency and the local-search trust-region approach (tDFTR) providing effective objective gains for a low number of cost function evaluations. tAPPS demonstrates robust performance across different problem formulations that can support exploration efforts, e.g., during a pre-drill design phase while multiple independent tDFTR runs can provide local tuning capability around established solutions in a time-constrained post-drill setting. Additional remarks regarding joint completion design optimization, comparison metrics, and relative algorithm performance given the varying problem formulations are also made.

The Impact of Autonomous Inflow Control Valve on Improved Oil Recovery in a Thin-Oil-Rim Reservoir

Summary Oil production from thin-oil-rim fields can be challenging as such fields are prone to gas coning. Excessive gas production from these fields results in poor production and recovery. Hence, these resources require advanced recovery methods to improve the oil recovery. One of the recovery methods that is widely used today is advanced inflow control technology such as autonomous inflow control valve (AICV). AICV restricts the inflow of gas in the zones where breakthrough occurs and may consequently improve the recovery from thin-oil-rim fields. This paper presents a performance analysis of AICVs, passive inflow control devices (ICDs), and sand screens based on the results from experiments and simulations. Single- and multiphase-flow experiments are performed with light oil, gas, and water at typical Troll field reservoir conditions (RCs). The obtained data from the experiments are the differential pressure across the device vs. the volume flow rate for the different phases. The results from the experiments confirm the significantly better ability of the AICV to restrict the production of gas, especially at higher gas volume fractions (GVFs). Near-well oil production from a thin-oil-rim field considering sand screens, AICV, and ICD completion is modeled. In this study, the simulation model is developed using the CMG simulator/STARS module. Completion of the well with AICVs reduces the cumulative gas production by 22.5% and 26.7% compared with ICDs and sand screens, respectively. The results also show that AICVs increase the cumulative oil production by 48.7% compared with using ICDs and sand screens. The simulation results confirm that the well completed with AICVs produces at a beneficial gas/oil ratio (GOR) for a longer time compared with the cases with ICDs and sand screens. The novelty of this work is the multiphase experiments of a new AICV and the implementation of the data in the simulator. A workflow for the simulation of AICV/ICD is proposed. The simulated results, which are based on the proposed workflow, agree with the experimental AICV performance results. As it is demonstrated in this work, deploying AICV in the most challenging light oil reservoirs with high GOR can be beneficial with respect to increased production and recovery.

Subsea Multilateral Oil Producer Evaluated With Acoustic and Production-Logging Tools

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 210299, “A Subsea Multilateral Oil Producer, Completed With AICD Sand Screens and Selective Inflow Valves, Is Evaluated by Combined Acoustic and Production-Logging Tools, Identifying the Sand-Producing Branch and a Tubing Leak in a Single Operation,” by Duncan Troup, SPE, Archer; Tim Griffin, SPE, Three60Energy; and Minh Pham, Aker BP, et al. The paper has not been peer reviewed. _ A horizontally completed subsea multilateral well exhibited unexpected sand production and a tubing leak, leading to the well being shut in. The complete paper discusses the novel tools and techniques used to localize the tubing leak, identify the bore responsible for sand production, and provide relative sand quantification at differing flow rates. Well Background and History The well was drilled and completed as a subsea producer to be tied back to an existing floating production, storage, and offloading (FPSO) vessel by means of a subsea flowline. After drilling of the first lateral, the decision was taken not to complete it. A second lateral was then drilled and completed. The main and secondary bores were drilled into different zones of the reservoir. Both lower completions used standalone sand screens, autonomous inflow-control-device nozzles, and swell packers set in open hole. Each of the lower completions was fitted with a hydraulically actuated inflow control valve (ICV) for managing production flow from the reservoir zones, providing the ability to produce each leg independently or commingle them. The upper completion is equipped with two gas lift valves (GLV) to provide artificial lift, a chemical injection mandrel, and a surface-controlled subsea safety valve (SCSSV). After approximately 6 months of flowing the well, water cut was seen to increase and a series of “popping” events occurred in which productivity increased markedly for short periods. Significant quantities of sand soon began to accumulate in the FPSO topside facilities. Approximately 1.5 years after startup, well productivity decreased sharply over a few months while the water cut continued to increase. As the productivity continued to decline, the leak rates exhibited by the SCSSV and one GLV fell outside the acceptable criteria. The pressure responses indicated a high leak rate. The well was shut in pending diagnostic logging and repair of the leak. Sand-Source Investigation The subsea wellhead of this well was fitted with an acoustic sand detector, but this had only indicated minor amounts of solids in the flowstream over the producing lifetime of the well. An extensive investigation concluded that the makeup of the collected sand was most likely to have originated in the case study well and that the amounts involved were likely to have been a contributing factor in the loss of well integrity. Because the well was producing from two different branches, a probability existed that only one of these was suffering from sand production. The well completion was designed to allow independent control of the branches by use of ICVs, so an intervention to assess the status of each of the branches with respect to water and sand production was planned, with the additional objective of diagnosing the well-integrity failure.

Autonomous Inflow Control Valve for Medium-Light Oil and Its Effective Performance

Summary Many horizontal oil wells will after a time start producing unwanted fluids. Autonomous inflow control valves may help to choke these unwanted fluids and consequently improve carbon efficiency. This paper publishes new experimental data describing how an autonomous inflow control valve manages medium-light oil (6 cp), water, and gas at reservoir conditions. A further objective is to evaluate how this valve might impact well performance under various conditions. To verify the single- and multiphase flow behavior of the valve, extensive flow loop experiments were performed. Initial testing was done in a model fluid laboratory, while a more extensive test was performed at reservoir conditions (i.e., with formation water, reservoir oil, and hydrocarbon gas at the given reservoir temperature and pressure). To explore and understand the impact of this valve for various reservoir scenarios, a simple conceptual reservoir model with realistic boundary conditions was used. At various differential pressures, the single-phase oil, water, and gas rates were measured. Performance at varying water and gas fractions was measured to get an improved understanding and knowledge of multiphase flow occurring in a well. The results show clearly that the valve will choke gas and water effectively, both at single-phase and multiphase flow conditions. The reservoir and model fluid evaluations show consistent results. The valve shows roughly a monotonic decreasing total rate with decreasing oil fraction, implying that the valve will always prioritize sections with the largest oil fraction. A mathematical model match of the valve performance is possible via the 10-parameter extended autonomous inflow control device (AICD) equation that enables practical evaluation of the valve in industry-standard reservoir simulators. Various scenarios are explored with a conceptual reservoir model, and the autonomous inflow control valve shows its capacity to reduce water production and enable a more gradual and controlled increase in gas/oil ratio for most scenarios. The autonomous inflow control valve shows its largest potential to reduce unwanted fluids and increase oil recovery when used in segmented reservoirs. In cases with uncertain aquifer and/or gas cap strength, or large variation in effective permeability, the valve will make an infill well more robust as it autonomously adapts to reality, chokes unwanted fluids, and consequently enables more carbon-efficient reservoir management.

Technology Focus: Completions (April 2023)

_ A few years ago, exaggerating a figure of speech, I coined the expression, “We work in a water industry; oil is just a supporting actor.” In fact, producing water is the final destination of every oil field, but obviously the objective was to highlight the importance of water management in the hydrocarbon-production process. Since the beginning, well completion and stimulation strategies have always sought to optimize water management and, extending the concept, management of all fluids produced. Selective completions in vertical and multilateral wells (combined with sand control or not) and segmentation of horizontal wells are good examples of this effort. These technologies, combined with intelligent completion, have brought very positive results. Intelligent completion in open hole, currently used in the Brazilian presalt, has allowed the reduction of the carbon footprint, so necessary nowadays. The optimal application of intelligent completion is the subject of paper SPE 209965, an excellent compendium of best practices on the topic. In recent years, driven by technological advances, good results, and the need to increase operational efficiency, we have experienced a major increase in the use of devices for flow equalization and selective fluid production [e.g., inflow control devices, autonomous inflow control devices (AICDs), and autonomous inflow control valves]. A significant reduction in water and gas production has been reported in several technical papers. In fact, this is the most published completion topic in the past 3 years, and many good articles are available. Apart from new and exciting trends, conventional solutions continue to play their important role. Basic themes long discussed continue to evolve and bring new insights. This is the case with paper SPE 204185, which deals with perforating for fracturing. Finally, paper SPE 210417 discusses the use of AICD technology in the Singue Field in Ecuador, which resulted in an increase in cumulative oil rate and a decrease in cumulative water. Recommended additional reading SPE 210205 Successful Autonomous Inflow-Control Device Application To Reduce Water Production in a Heavy Oil Greenfield by Carlos A. Pedroso, Enauta, et al. SPE 206213 Automated Well Production and Gas Lift System Diagnostics and Optimization Using an Augmented Artificial Intelligence Approach in a Complex Offshore Field by Mahmoud Elwan, Dragon Oil, et al. OTC 31483 Case Study: How the Newest Generation of Autonomous Inflow Control Devices Helps To Control Excessive Well-Water Production Within a Major Sultanate of Oman Oilfield by Salim Buwauqi, Petroleum Development Oman, et al.

Technology Focus: Water Management (December 2022)

2022 has presented many challenges—not just inflation. Lowering water levels at Lake Mead and Lake Powell resulted in water crises in many states. Globally, many rivers dried, and that brought to surface over-5,000-year-old archeological artifacts that had been buried. An United Nations report says that nearly 4 billion people (approximately 60% of the world population) face water crises at least for a month every year. Despite all these admonishments, water—an essential raw material in industrial sector and a vital resource for human living—could be handled with more value and respect. The dollar value of water usage is much lower in the US compared with other regions, where it is more than twice its purchased value. The last 30 years or so have seen scientists and environmentalists apply conscientious use of technologies that focused on making water resources sustainable—chemistries that help us treat water, and intuitive and intelligent technologies that minimize need and maximize its purpose and benefit, remove contaminants, and ready it for repurposing. We can agree that awareness is universal, but when it comes to enforcing the actions needed to protect the resource as sustainable, questions about scalability and economic feasibility of many of the novel technologies arise. The three papers chosen for publication share different approaches to chemically managing high-salinity produced water through commercially viable approaches. The identification of processes to treat high salinity levels and the approaches to alter and control the process make the papers not only good for discussion but also practical for all players, big and small. The introduction of chemistries that are tagged and measurable positively influence discharge restrictions in different regions and could be exploited to stretch water reuse and the dollar value of water. The advent of smart sensors, probes, handhelds such as portable X-ray fluorescence and X-ray diffraction sensors, and machine learning make the treatment and reuse of high-saline water feasible to alleviate the water crisis. Technologies have advanced to lower the energy consumption and usage cost of membrane separation most commonly used in the water-reuse sector. The use of fresh water by the industry could be reduced significantly with the adaptation of some or all the smart technologies available today. The industry and the public are at a crossroads today, fighting for the right to use water. Governments are struggling to keep the balance and make the scarcest resource available to both sides. Let there not be another Akkadian empire that becomes extinct because of water. Recommended additional reading at OnePetro: www.onepetro.org. SPE 200171 Optimizing Waterflood Performance in Mature Fields Using Autonomous Inflow Control Valve Technology by Sufyan Shihab, Petroleum Development Oman, et al. SPE 209256 Improved Reverse-Osmosis Membranes for Treating Produced Water by Rich Franks, Nitto-Hydranautics, et al. SPE 204840 A Nano Method for a Big Challenge: Nanosilica-Based Sealing System for Water Shutoff by Ayman Almohsin, Saudi Aramco, et al.

Life-Cycle Production Optimization of the CO2-Water-Alternating-Gas Injection Process Using Least-Squares Support-Vector Regression Proxy

SummaryIn this study, we present a framework for efficient estimation of the optimal carbon dioxide (CO2)-water-alternating-gas (WAG) parameters for robust production-optimization problems by replacing a high-fidelity model with a least-squares support-vector regression (LS-SVR) model. We provide insight and information on the proper selection of feature space and training samples of the LS-SVR proxy model for the CO2-WAG life cycle production optimization problem. Given a set of training points generated from high-fidelity model-based simulation results, an LS-SVR-based proxy model is built to approximate a reservoir-simulation model. The estimated optimal design parameters are then found by maximizing net present value (NPV) using the LS-SVR proxy as the forward model within an iterative-sampling-refinement (ISR) optimization algorithm that is designed specifically to promote the accuracy of the proxy model for robust production optimization. As an optimization tool, the sequential quadratic programming (SQP) method is used. CO2-WAG design variables are CO2 injection and water injection rates for each injection well at each cycle, production bottomhole pressure (BHP) for each production well at each WAG half-cycle, and inflow control valve (ICV) for each well at each WAG half-cycle and at each valve. We study different scenarios where we fix some of the design variables to investigate the importance of design variables on the life cycle production optimization of the CO2-WAG problem. We compare the performance of the proposed method using the LS-SVR runs with the popular stochastic simplex approximate gradient (StoSAG) and reservoir simulation runs for a synthetic example considering a three-layer, channelized reservoir with four injectors and nine producers. Results show that with the properly selected feature space and training points, the proposed LS-SVR-based ISR optimization framework is at least 1.5–8 times computationally more efficient, depending on the cases considered, than the StoSAG using a high-fidelity numerical simulator. However, we observe that the size and sampling of the training data, as well as the selection of well controls and their bound constraints for the well controls, seem to be influential on the performance of the LS-SVR-based optimization method. This is the first LS-SVR application to the CO2-WAG optimal well-control problem. The proposed LS-SVR-based ISR optimization framework has the potential to be used as an efficient tool for the CO2-WAG optimization problem.

Evaluating the performance of advanced wells in heavy oil reservoirs under uncertainty in permeability parameters

Advanced wells play a crucial role in maximizing the efficiency of oil production. To achieve a successful design for advanced wells, several parameters must be considered and evaluated. Uncertainty in these parameters can have a significant impact on the performance assessment of the well in its lifetime. Absolute permeability, relative permeability, and permeability anisotropy are the parameters that determine reservoir permeability and are among the most important design parameters to be considered. This paper aims to assess the performance of advanced wells completed with passive and reactive downhole Flow Control Devices (FCDs) under uncertainty in the reservoir permeability parameters. The assessment is conducted through a case study on a synthetic heavy oil reservoir with a strong water drive. The EclipseSM reservoir simulator is used as a simulation tool and the Latin Hypercube Sampling (LHS) approach is applied as a sampling tool for uncertainty analysis in this study. According to the obtained results, under the presence of uncertainty, advanced wells with Autonomous Inflow Control Device (AICD) and Autonomous Inflow Control Valve (AICV) completions are able to mitigate the risk of water production by 53.20% and 71.12% respectively compared to conventional wells. However, Inflow Control Device (ICD) completion can only reduce the risk by 0.87%.

Study of polymer flooding and intelligent well technology for improved oil recovery

The application of Intelligent Well Technology (IWT) to improve efficiency of a polymer flooding operation has been studied under three cases using a 3D model implemented in reservoir simulation software. The base case was the simulation study of a polymer flood with a relatively low oil recovery, which led to the least produced water into the producer well. The second case was incorporating IWT into the producer well where production control was achieved via the operation of inflow control valves (ICVs) installed in each productive segment of the wells. The reactive control strategy responded to changes in segment water cut, which led to improved sweep and, hence, oil recovery at 63 %. A third case was considered where injection control was performed via the same conditions as the producer well but, in this instance, the outflow control valves (OCVs) responded to changes in water cut at the injection wells. This oil recovery under injection control also improved to 68 %, but with higher water cuts. The study results showed that a better sweep of oil is possible despite the high water cuts when downhole segment conditions are adequately responded to. Thus, concluding that polymer flooding can be improved by incorporating IWT through production or injection control for a multi-layered heterogeneous reservoir.

Using Smart Completion Technology to Control Water Coning Problems and Increase Oil Recovery in a Southern Iraqi Oilfield

This research describes the using of a new well completion technology system that enhance the homogeneous and heterogeneous reservoir deliverability and the production performance gained through a completion technique using Autonomous Inflow Control Valve (AICD) by self-decreasing/delaying water and gas progress and promoting increasing in oil production, therefore, equalizing the drawdown (∆P=Pi-Pwf) along the well and provide a dynamic water shut-off operation and significantly increasing the economic life of a well and therefore, reducing capital and operational expenditures for the field development.
 The research presents a production performance simulation results for a conventional and smart well completion technology in a horizontal well in a southern Iraqi oilfield for two stages during well life; early stage (till 2018) and late stage (till 2033). For early stage of well life, there was no significant difference in results when comparing between the conventional completion design and the smart completion design. In the contrast, the simulation results for the late life of the well showed that the well can produce for approximately 1056.7 barrel per day crude oil with a water-cut of 82 % at the year of 2033. The also revealed that the results showed that the cumulative oil production from the year of 2018 till 2050 will be 23 million barrel of crude oil and 44 million barrel of water when the well is completed with conventional completion design. When the completion design has been changed and equipped with autonomous inflow control devices (AICDs) technology and simulated the production performance by NETool Software. The simulation results showed that the oil production has been increased by 891 barrel per day (1947.3 barrel per day) and the water cut has reduced significantly in comparison with the conventional production completion by 17 % (65.4 %) at the year of 2033. The results revealed that the cumulative oil production from the year of 2018 till 2050 will be 31 million barrel of crude oil and 33 million barrel of water.
 It has been concluded, from the reservoir and production simulation, that the application of the technology is successful and showed a clear advantage of using Autonomous Inflow Control Device (AICD) that provides better water influx control profile.

Autonomously Controlling the Conformance of Injection-Well Fluids

As production declines over time, the injection of fluids is required to enhance oil recovery and/or maintain the reservoir pressure. Whether applied at field startup or as a secondary recovery technique, waterflooding can boost oil recovery from less than 30% to 30–50%. The common problems associated with waterflooding include loss of injectivity, premature injector failure, and injection conformance. This can also lead to issues around insufficient voidage replacement, which can result in lower reservoir pressure and the production of fluid with a higher gas/oil ratio. In total field recovery, this ultimately means lower production and oil left untapped in the well. To remediate the issue of conformance, costly and often complex interventions and redrills were traditionally used to restore water-injection capability. Also, passive outflow-control devices have been used successfully to somewhat improve the fluid conformance from injection wells. However, they may fail in reservoirs with complex/dynamic properties including propagating/dilating fractures. Advanced Wells in Injection Wells There are a number of considerations when planning a water-injection completion, particularly around both the rock and fluid properties, as well as the credible risks that could occur, namely: - Uneven displacement of hydrocarbon - Fracture growth short-circuiting injectant-proximal wells - Fracture growth breaching caprock/basement seal - Crossflow, plugging, and solids fill Advanced completion options include deploying passive flow-control devices. For example, inflow-control devices (ICDs) are unable to react to dynamic changes in reservoir/well properties. This often requires production-logging-tool (PLT) logs, distributed temperature sensors, and/or tracers to be run and, if available, to apply the sleeve option. Alternatively, active (intelligent) completions, such as inflow-control valves, can be used, but they tend to be expensive and complicated and are limited to the number of zones. This technique also requires frequent analysis of data from the well to perform such actions. Tendeka, a global specialist in advanced completions, production solutions, and sand control, has developed FloFuse, a new and exclusively autonomous rate-limiting outflow-control device (AOCD) (Fig. 1). Using the analogy and inspiration of a home fuse box, which contains many individual fuses to control various parts of a building, the AOCD can control the excessive rate that passes through a specific section of a well, causing tripping once the threshold is reached. By almost shutting, i.e., significantly choking, the injection fluid into the fractures crossing the well, the AOCD autonomously prevents growth and excessive fluid injection into the thief/fracture zones and maintains a balanced or prescribed injection distribution. Like other flow-control valves, this device should be installed in several compartments in the injection well. Initially, devices operate as normal passive outflow control, but if the injected flow rate through the valve exceeds a designed limit, the device will automatically shut off. This allows the denied fluid to that specific compartment to be distributed among the neighboring compartments.

Model‐based multi‐objective particle swarm production optimization for efficient injection/production planning to improve reservoir recovery

AbstractThis study employs an adjusted version of the multi‐objective particle swarm optimization (MOPSO) algorithm to plan an optimized reservoir's injection/production strategy. Three case studies, including two water‐flooding benchmark models and one gas‐condensate problem, are exercised as subjected problems to validate the MOPSO approach. The contradicting values of objectives, long‐term net present value (LNPV) versus short‐term net present value (SNPV), are obtained so that relying on a Pareto front improves decision‐making. In one water‐flooded case, inflow control valves of smart wells are considered to be adjusted within the optimization, while in the second case, the optimized well injection rates are control variables. The obtained results for water‐flooded reservoirs are shown to optimize the competitive objective functions more than the previous efforts in the literature. Moreover, 10 different permeability maps of the second case are implemented to obtain the optimum injection rates to perform optimization under uncertainty. The MOPSO robustly optimized the production/injection strategy in the presence of model uncertainty. In the gas‐condensate problem, the optimal gas injection rate in the SPE‐3 benchmark model is determined. The gas‐condensate case's outputs yield a decreased oil saturation result in the reservoir compared to non‐optimized production scenarios. Results illustrate that for all cases, MOPSO can provide optimal injection/production scenarios. Therefore, the proposed scheme gives the advantage of deciding between the set of results into a decision‐maker to optimize the production program by trading‐off within different strategies. Besides the Pareto fronts with adequate variety and steadiness, a great converging rate is the main advantage of this method.

Design to First Deployment: Pressure-Activated Sliding Sleeve for Single-Trip Completion

Summary Interest is high in a method to reliably run single-trip completions without involving complex/expensive technologies (Robertson et al. 2019). The reward for such a design would be reduced rig time, safety risks, and completion costs. As described herein, a unique pressure-activated sliding side door (PSSD) valve was developed and field tested to open without intervention after completion is circulated to total depth (TD) and a liner hanger and openhole isolation packers are set. A field-proven sliding-sleeve door (SSD) valve that required shifting via a shifting tool run on coiled tubing, slickline (SL), or wireline was upgraded to open automatically after relieving tubing pressure once packers (and/or a liner hanger) are set. This PSSD technology, which is integrable to almost any type of sand control screen, is equipped with a backup contingency should the primary mechanism fail to open. Once opened, the installed PSSDs can be shifted mechanically with unlimited frequency. The two- or three-position valve can be integrated with inflow control devices (ICDs) (includes autonomous ICDs/autonomous inflow control valves) and allows mechanical shifting at any time after installation to close, stimulate or adjust ICD settings. After a computer-aided design stage to achieve all the operational/mechanical requirements, prototypes were built and tested, followed by field installations. The design stage provided some challenges even though the pressure-activation feature was being added to a mature/proven SSD technology. Prototype testing in a full-scale vertical test well proved valuable because it revealed failure modes that could not have appeared in the smaller-scale laboratory test facilities. Lessons learned from the first field trial helped improve onsite handling procedures. The production logging tool run on first installation confirmed the PSSDs with ICDs opened as designed. The second field installation involved a different size and configuration, in which PSSDs with ICDs performed as designed. The unique two- or three-position PSSD accommodates any type of sand control or debris screen and any type of ICD for production/injection. The PSSD allows the flexibility to change ICD size easily at the wellsite. Therefore, this technology can be used in carbonate as well as sandstone wells. Wells that normally could not justify the expense of existing single-trip completion technologies can now benefit from the cost savings of single-trip completions, including ones that require ICD and stimulation options.

Surrogate-Based Prediction and Optimization of Multilateral Inflow Control Valve Flow Performance with Production Data

Summary Smart completions enable physical measurements over space and time, which provides large volumes of information at unprecedented rates. However, optimizing inflow control valve (ICV) settings of smart multilateral wells is a challenging task. Traditionally, ICV field tests, evaluating well performance at different ICV settings, are conducted to observe flow behavior and configure ICVs; however, this is often suboptimal. This study investigated a surrogate-based optimization algorithm that minimizes the number of ICV field tests required, predicts well performance of all unseen combination of ICV settings, and determines the optimal ICV setting and net present value (NPV). A numerical model of a real offshore field in Saudi Arabia was used to generate scenarios involving a two-phase (oil and water) reservoir with trilateral producers. Multiple scenarios were examined with variations in design parameters, mainly well count, placement, and configuration. Eight discrete settings were assumed to match the commonly installed ICV technology, where all possible scenarios were simulated to establish ground truth. The investigation considered three major algorithmic components: sampling, machine learning, and optimization. The sampling strategy compared physics-based initialization, space-filling sampling, and triangulation-based adaptive sampling. A cross-validated neural network was used to fit a surrogate (in this case, machine learning algorithm) dynamically, whereas enumeration was adopted for optimization to avoid errors arising from using common optimizers. This study evaluated two sampling techniques: space-filling and adaptive sampling. The latter was found superior in capturing reservoir behavior with the smallest number of simulation runs (i.e., ICV field tests). Algorithm performance was evaluated based on the number of ICV field tests required to exceed an R2 threshold of 90% on all unseen scenarios and match the optimal ICV settings and NPV. Surface and downhole flow profile prediction and optimization were achieved successfully using this approach. To determine the diminishing value of additional ICV field tests, the triangulation sampling loss was used as a stoppage criterion. When running the algorithm on a single producer for both surface and downhole oil and water flow prediction, the algorithm required only 6 and 11 ICV field tests to achieve 80% and 90% R2 across the different cases of this real reservoir model. Fishbone wellbore configurations were found to pose a more challenging task because changes in any ICV pressure decrease affects multiple laterals simultaneously, which increases the level of interdependence. The resultant surrogate was used to decide on the optimal settings of ICV devices and effectively predict the NPV. Surrogates, in this approach, are statistical proxies of the targeted ground-truth production function. Further improvement was accomplished through adaptively sampling and fitting surrogates to predict NPV explicitly, where NPV predictions were generated with nearly 95% R2 given only 10 ICV field tests. Using adaptive sampling and machine learning proved effective in the prediction of surface and downhole flow profiles and optimization of smart wells. The method further allows for dynamically optimizing field strategy in a reinforcement learning setting where production data are used continuously to further improve the prediction performance.

Model-based water-flooding optimization using multi-objective approach for efficient reservoir management

The efficient development of an oil field mostly depends on a comprehensive optimization of subsurface flow. To account for several discrete or even contradicting objectives, multi-objective optimization (MOO) approach presents multiple optimum solutions for decision-making processes. There are excessive degrees of freedom in any optimization problem of the life-cycle of water-flooding to optimize the short-term performance during the process. Choosing each strategy has a different impact on the long-term reservoir performance. Thus, in this study, we have utilized two different model-based algorithms based on multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II) methods with some modifications to plan the short- and long-term production strategies simultaneously in water-flooded reservoirs. These algorithms are both population-based techniques, in which the Pareto-ranking approach is combined with the inherent search towards the optimal solution for a multi-criterion optimization problem. Maximizing the long-term Net Present Value (LNPV) and short-term (discounted) NPV (SNPV) are the objectives to be met in the investigated MOO problems. To address the imperfect Pareto front obtained in MOO problems, some modifications have been added to the utilized algorithms, including using a modified comparison operator in the NSGA-II method and employing the crowding distance parameter in the leader selection process together with a revised archive controller as well as a dynamic boundary search to MOPSO algorithm. By these means, the entire Pareto fronts are actively generated, which covers the complete solutions area through both algorithms. To validate the developed approaches, two benchmark water-flooded reservoir models have been employed. In the first case, the optimization parameters are the wells injection rates in the Egg benchmark reservoir model. In the second one, we have adjusted the opening values of the inflow control valves (ICV) of smart wells in the water-flooding process of a layered reservoir with a five-spot pattern. The effect of the trading-off between Pareto elitism and diversity on the final results is investigated for both algorithms. Results illustrate that the competitive values of the NPV functions, LNPV and SNPV pairs, lying on the obtained Pareto front, provide a promising criterion to improve the decision-making process. A comparison of various methods shows that for both case-studies, MOPSO can strongly propose a production strategy that more appropriately optimizes SNPV and LNPV compared to the NSGA-II as well as compared to some previous efforts published in the literature. A high rate of convergence, together with the logical Pareto front having enough diversity and uniformity, and also the independency of the final solution on the initial guess, are the main advantages of MOPSO in comparison with other approaches.

Autonomous Valve Controls Excess Water, Gas Production To Increase Oil Recovery

Increasing sensitivity to oil price fluctuation requires operators to reduce costs of operation. A key component is collaborative management by operators and suppliers to reduce cost over the full life cycle of the operation. Much of the focus is on the equipment-purchasing strategy; nonetheless, effective technology such as an autonomous inflow control valve could also benefit the operating expenditure (OPEX) savings by enhancing oil recovery and reducing processing costs of excessive unwanted water and gas in surface facilities. OPEX comprises labor, chemicals, consumables, infrastructure maintenance, transportation, disposal, and other utilities. Capital expenditure (CAPEX) may also be reduced for long-term projects, which generally comprise infrastructure such as pipelines, pumps, disposal wells, ponds/storage treatment facilities, and other associated utilities infrastructure. The average cost for handling produced water starts from about $1.50/bbl, depending on the geographical location of the operation. Such costs may justify an assessment of an autonomous inflow control valve (AICV) to reduce unwanted water and gas to achieve OPEX savings. Horizontal wells are a proven option to maximize reservoir contact in certain situations. A challenge is often early water breakthrough in less than 6 months from starting production, and then progressively producing very-high water cuts, often 95%, for long periods of times thereafter. Inflow control device (ICD) technology has demonstrated potential in improving recovery in horizontal oil wells by delaying the gas and/or water breakthrough. However, ICDs cannot restrict water effluents once breakthrough occurs. A new generation of inflow control technology known as an AICV can balance the production flow and choke and shut the water-effluent zones once breakthrough occurs. Basis of Design The design is based on the Hagen-Poiseuille equation and Bernoulli’s principle. It uses the difference in fluid-flow behavior in the laminar- and the turbulent-flow restrictor to differentiate the pressure drop using the mobility ratio between oil, water, and gas. Light-viscosity fluids such as water and gas have high mobility and allow the AICV to detect the mobility difference, then choke and shut the main inflow area in the valve autonomously. Fig. 1 illustrates the construction of the valve in open positions, showing the direction of flow with arrows and the P1, P2, and P3 pressure locations. The inlet pressure is represented by P1: 2-5% of the main flow will move through the laminar-flow element (LFE) that will reduce the pressure to P2. Further pressure reduction occurs in the turbulent-flow element (TFE) to P3 as the tubing pressure. The differential pressure in LFE reacts to the piston’s effective area, resulting in a force balance around the piston to control the valve’s function (e.g., to open, choke, or close the main flow).