Autonomous Inflow Control Device Research Articles

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%.

Matrix Injectivity Achieved in Deepwater Gas-Injector Wells

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 208809, “Deepwater Gas-Injector Wells: Overcoming the Challenge of Achieving Matrix Injectivity,” by Cedric Manzoleloua, Chau Nguyen, SPE, and Albert Okhrimenko, SPE, Schlumberger, et al. The paper has not been peer reviewed. After a successful exploration phase, an opportunity to develop the Guyana Suriname Basin came to fruition. The drilling and completion campaign scope included planned gas-injector wells that required a breaker application for matrix injection. A reversible nonaqueous reservoir drill-in fluid (RDIF) system using a calcium bromide brine as the internal phase and formulated at a 50/50 oil/water ratio (OWR) was selected. The complete paper discusses the results of extensive laboratory tests for the selection, customization of both the RDIF and the delayed breaker, and the field performance of the two fluids. Introduction All wells in the field were completed either as openhole gravel-pack or stand-alone screen configurations using inflow control devices (ICDs) or autonomous ICDs (AICDs). The gas-injector wells were completed as standalone completions with ICDs. The primary objective of the gas-injector wells was to put the wells on direct injection with no opportunity to flow back or fracture the formation.

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.

Technology Focus: Heavy Oil (April 2022)

Heavy oils are characterized by high density, high viscosity, and high-heavy-fraction components. Because of high viscosity and lower API gravity than conventional crude oil, primary recovery of some of these crude oil types requires thermal stimulation of the reservoirs. Most of the technologies that deal with heavy oil need to address the mobility ratio or viscous forces before any flooding. In general, poor recovery is caused by physical reasons or geological reasons. Physical reasons can be categorized as capillary forces (existence of the interfacial tension between oil and water, wettability) or viscous forces (high mobility ratio between water and oil). Geological reasons are heterogeneities in reservoir rock and exist in all petroleum oil systems. In heavy oil reservoirs, enhanced oil recovery (EOR) intends to reduce the capillary forces and interfacial tension to improve microscopic displacement efficiency or improve the sweep efficiency (macroscopic) by reducing the mobility ratio between injected fluid and displaced fluid. Improving the mobility ratio is achieved by increasing the viscosity of water using polymers or by reducing the oil viscosity using heat. In general, all technologies need to address the capillary and viscous forces to improve oil recovery. Paper SPE 207361 discusses improving of the efficiency of the flood by near-wellbore conformance and improving the vertical sweep efficiency. The use of fiber-optic sensors, as addressed in paper SPE 199023, is intended to gather better data and avoid misinterpretation during falloff tests and injectivity tests. Traditionally, for heavy oil EOR simulation, because of the addition of chemical species or heat to the flow equations as well as the need for a finer grid resolution, the use of the full-field model in most cases was limited and the use of sector models and local grid refinement to obtain a reasonable accuracy has been applied in the industry. Sector modeling conditions must be satisfied to establish the reliability and the trade-off between accuracy (sector models) and computational expediency (full-field model). Recent development of hardware and software [graphics-processing-unit (GPU) -based simulators] has provided the industry with the tools to achieve a full-field model simulation in most fields by taking advantage of GPU solvers and using a fine-grid model to predict full-field performance. Recommended additional reading at OnePetro: www.onepetro.org. SPE 200279 - Field Application of the Autonomous Inflow Control Device for Optimized Heavy Oil Production in South Sultanate of Oman by Ali Al-Jumah, Petroleum Development Oman, et al. SPE 203012 - More Oil and Less Water: Autonomous Inflow Control Devices in New and Old Producers in Heavy Oil Fields From South of Oman by Ameera Al Harrasi, Petroleum Development Oman, et al. SPE 207684 - Game Changer in Dealing With Hard Scale Using a Slickline Torque Action Debris Breaker by Mahmoud Mohamed Koriesh, Dragon Oil, et al.

Extended-Reach Wells Help Optimize Production in Marginal Offshore Prospects

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 202896, “Optimizing Production From Marginal and Challenging Prospects To Unlock Field Potential: Success Cases in the Jasmine Field, Gulf of Thailand,” by Mukminin Yusuf, SPE, Pattarapong Prasongtham, SPE, and Theeranun Limniyakul, SPE, Mubadala Petroleum, et al. The paper has not been peer reviewed. The development of marginal volumes in the Jasmine field is part of the operator’s strategy to extend the field’s life, involving the exploitation of increasingly challenging prospects. The complete paper highlights two case studies to illustrate how the operator has developed marginal prospects to unlock the Jasmine field’s remaining potential successfully. The use of autonomous inflow control devices (AICD) has played a significant role in optimizing production in reservoirs with small oil rims and thick gas caps. Jasmine Field The designation “Jasmine field” is commonly used to refer to both the Jasmine field and the neighboring Ban Yen field, which are essentially one integrated field from an operational perspective. The fields are in the Gulf of Thailand, approximately 300 km southeast of Bangkok in depths of 190 to 200 ft (Fig. 1).

Technology Focus: Mature Fields and Well Revitalization (January 2022)

The highlight of this year’s feature on mature fields and well revitalization has been the increasing use of artificial intelligence (AI) and machine learning (ML) for analysis of mature assets. Many paper proposals studied using AI/ML techniques cover a wide range of topics including optimization of production operations, faster reservoir characterization of mature fields, and improvement of ongoing waterfloods. In fact, increased use of AI/ML has been a recurring theme in many of the areas covered in the Technology Focus sections of 2021’s JPT issues. There has also been a focus on implementing novel technologies such as the use of autonomous inflow-control devices in horizontal wells to suppress ingress of unwanted fluids in thin-oil-rim reservoirs, using integrated-asset models for debottlenecking, and the use of cased-hole logging in old wells to look for missed opportunities. After serving for 5 years, my time for writing this column is coming to an end. It has been a highly rewarding exercise going through the paper proposals, experiencing the hard work put in by industry professionals to arrest inevitably declining production from mature assets by putting together ideas in diverse fields such as reservoir management, production optimization, drilling, and formation evaluation to produce the extra barrel from mature brownfields. Out of the 314 paper proposals studied in these 5 years, 137 (44%) dealt with waterflood improvement, reservoir characterization, and simulation, and approximately 78 papers (25%) dealt with well revitalization involving workover drilling, completion, and stimulation. Sustaining production from mature brownfields challenges the best from each discipline, and significant success stories have come from a genuine collaboration of ideas across disciplines from subsurface to engineering. Recommended additional reading at OnePetro: www.onepetro.org. SPE 206195 - Data-Driven Optimization of Intermittent Gas Production in Mature Fields Assisted by Deep Learning and a Population-Based Global Optimizer by Javier Fatou Gómez, TNO, et al. SPE 205546 - Role of Geomechanics in Identification of Possible Mechanisms for Nonproductive Time and Improving Drilling Operations in a Mature Field in Offshore Sarawak, Malaysia by Avirup Chatterjee, Baker Hughes, et al. SPE 206303 - Combining Capacitance Resistance Model With Geological Data for Large Reservoirs by Davud Davudov, Resermine, et al.

Application of mathematical and machine learning models to predict differential pressure of autonomous downhole inflow control devices

Controlling reservoir fluid flow is important for maximizing petroleum production through wellbores. A major challenge that reduces the production of oil is early breakthrough of secondary fluids to the wellbore perforations. This occurs due to the low viscosity of gas and water relative to oil, and the heterogeneity of reservoir permeability. Autonomous inflow control devices represent a new self-regulating technology that helps to increase petroleum production, particularly oil, by restricting the production of unwanted fluids like gas and water into the wellbores. This study develops smart systems based on machine learning models to predict the performance of autonomous inflow control devices. Several machine learning models are evaluated including adaptive neuro fuzzy inference system, hybrid adaptive neuro-fuzzy inference system genetic algorithm, artificial neural network and support vector machine and their prediction performance is compared to that of linear regression, full quadratic regression model and the mathematical autonomous inflow control device performance model. Each model is developed to estimate the differential pressure of Equiflow autonomous inflow control devices based on ninety experimentally recorded data records. The range of equiflow autonomous inflow control device, viscosity, density and flow rate are the input variables and differential pressure is the output dependent variable of each model. The prediction accuracy of the models is assessed in terms of several standard statistical accuracy performance measures. These performance indicators confirm that the machine-learning models provide superior prediction accuracy for autonomous inflow control device differential pressure. Overall, the support vector machine achieves the most accurate predictions of all the models evaluated recording root mean square error of 0.14 Mpa and coefficient of determination of 0.98. On the other hand, the linear regression model records the lowest prediction performance, highlighting the non-linearity of the autonomous inflow control device processes. Cited as: Yavari, H., Khosravanian, R., Wood, D.A., Aadnoy, B.S. Application of mathematical and machine learning models to predict differential pressure of autonomous downhole inflow control devices. Advances in Geo-Energy Research, 2021, 5(4): 386-406, doi: 10.46690/ager.2021.04.05

Autonomous Inflow-Control Devices Boost Production While Managing Sand

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 30403, “Sand Production Management While Increasing Oil Production of a Gravel-Packed Well Equipped With Rate-Controlled-Production Autonomous Inflow-Control Devices in a Thin Heavy-Oil Reservoir Offshore China,” by Shuquan Xiong, Fan Li, and Congda Wei, CNOOC, et al., prepared for the 2020 Offshore Technology Conference Asia, originally scheduled to be held in Kuala Lumpur, 2–6 November. The paper has not been peer reviewed. Copyright 2020 Offshore Technology Conference. Reproduced by permission. A 2018 infill development campaign for a horizontal well offshore China targeted improved production through the installation of autonomous inflow-control devices (AICDs). However, because the well requires gravel packing to manage the sand, the integration of AICDs and the gravel pack was an issue. An integrated work flow was followed to deliver the AICD application successfully in an offshore heavy-oil reservoir with major uncertainties in remaining oil thickness and water/oil contacts. AICD completions ensured balanced contribution from all reservoir sections and limited water production significantly while the gravel pack kept the valves safe from the effects of sand. Field Description The field is a low-amplitude fault anticline oil field developed on the basement uplift. The structure is relatively gentle (Fig. 1). The reservoir lithology is mainly feldspathic quartz sandstone, with an average porosity of 22%, an average permeability of 397 md, a reservoir pressure coefficient of 1, an oil density of 0.92 g/cm3, and crude oil viscosity of 150 cp. The current methodology for gravel packing with ICDs/AICDs in the well uses a multiple alpha-wave technique whereby at least one conventional standalone screen joint is deployed at the toe of the well to provide a return path during the buildup of the alpha wave. The flow rate is reduced progressively to maximize the dune weight until screenout is observed. Once the gravel-packing operation is complete, the standalone-screen section at the toe is isolated before the well is placed on production. This technique does not allow a complete pack to be achieved and will allow more gravel to build up around the zonal isolation packers. This methodology is most applicable in unconsolidated sands with high net-to-gross reservoirs where borehole collapse will occur early in well life. One technique to provide sufficient flow path through the screen assembly is to integrate sliding sleeves into each screen joint. However, in long lateral wellbores, this may be prohibitively expensive and requires multiple manual manipulations as the wash pipe is retrieved. The use of a temporary bypass valve is recommended to enable standard gravel-packing operations to be performed with ICDs without significant additional cost, complexity, or compromise. The dissolvable material is used with a valve located within the ICD/AICD housing to provide a high-flow-area path from the annulus to the tubing during completion operations.

A Proposed Method for Simulation of Rate-Controlled Production Valves for Reduced Water Cut

SummaryIn recent years, the advancement of horizontal-well technology has played a major role in making oil production economically feasible from many reservoirs. One of the major problems that can reduce the efficiency of using horizontal wells is gas and water coning caused by the heel-toe effect and heterogeneity along the well. To tackle this problem, Equinor’s autonomous inflow-control device (ICD) (AICD), known as rate-controlled production (RCP) valves, is widely used today. RCP valves can effectively delay the early water breakthrough and partially choke back water autonomously after water breakthrough. To fulfill a suitable design of a long horizontal well with the RCP completion, a detailed understanding of multiphase-flow behavior from the reservoir pore to the wellbore and production tubing is needed. Coupling a dynamic multiphase-flow simulator such as the OLGASM (Schlumberger Limited, Sugar Land, Texas, USA) simulator with the near-wellbore reservoir module such as the OLGA ROCX module provides a robust tool for achieving this purpose. However, there is no predefined option in the OLGA simulator for implementing the autonomous behavior of the RCP valves directly. Therefore, creating a model of oil production by considering well completion with the RCP valves in the OLGA simulator is challenging. In the previous works, this has been performed by using the Proportional Integral Derivative (PID) Controller option in the OLGA simulator, which controls the opening of an equivalent orifice valve according to the fixed value of the water cut. However, because of the performance of the PID Controller using a fixed setpoint and the difficulties in properly tuning the PID Controller, choosing this option leads to a large degree of inaccuracy in the simulation models. In this paper, by proposing a novel method with a developed mathematical model and a control function for the RCP valves, the autonomous behavior of these valves is implemented in the OLGA simulator. In this new approach, the control signals are calculated using the variation of water cut and introduced to the OLGA simulator through the Table Controller option instead of the PID Controller. The presented approach in this paper can be used for the simulation of water-cut (or gas/oil-ratio) reduction potential of all RCP-type AICDs in reservoirs with different characteristics. However, to explain the procedure of this approach in detail, the near-well oil production from Well 16/2-D-12 in the Johan Sverdrup Field (JSF) considering RCP completion is modeled as a case study. In this study, the simulation model is developed using one of the commonly used types of RCP valves called the TR7 RCP valve. Version 2016.1.1 of the OLGA simulator/ROCX module is used (Schlumberger 2016). According to the simulation results, compared with using ICDs, by the completion of Well 16/2-D-12 with RCPs, the water cut, water-flow rate, and accumulated water production can be reduced by 2.9, 13.3, and 12.1%, respectively, after 750 days. The results also showed that by using the proposed approach, the autonomous behavior of the RCP valves according to the water-cut variations can be appropriately implemented in the OLGA simulator. This can help engineers and researchers to achieve a better design of a long horizontal well using the RCP completion. Consequently, using this approach can be beneficial for improving technology, optimizing production, minimizing risk, and reducing costs in oil recovery.

Technology Focus: Heavy Oil (April 2020)

Technology Focus Reviewing a myriad of papers presented at different conferences during the past year and attending some of those to hear the oral presentation versions, I can group the current trends in heavy-oil operations and research into two major categories: Process optimization and use of chemicals as additives to steam and water. Here are some highlights from those categories. Several papers focused on purely computational methods—including multi-objective optimization and proxy models—to optimize the steam-assisted gravity drainage (SAGD) method with specific attention on preferential steam allocation. Real-life examples of these applications consist of inflow- and outflow-control devices and steam splitters developed for diverting the steam to preferential zones, thus minimizing the use of steam. As an indirect meth-od to provide supplemental data for the optimized solutions, seismic data were also used. Applications of seismic waves include the depiction of steam-chamber development and monitoring wellbore integrity. Considering that many SAGD operations are reaching maturity, these applications will help maintain the steam/oil ratios at low levels, therefore extending the life of the processes. In another group of studies, chemical additives were tested at the laboratory scale to improve cold (microemulsion formulations) and thermal (to reduce steam/oil ratio) heavy-oil recovery. Examples of newly trialed chemicals include ionic liquids, foam additives, anionic and hydrophobic surfactants, switchable-hydrophilicity tertiary amines, nano-fluids (dispersed SiO2 and ZrO2), ethers, alcohols, and chelating agents as steam additives and microemulsion formulations using SiO2, anionic and nonionic surfactants as well as deep eutectic solvents for cold production. Although most of the listed optimization studies (specific examples reported include the Mackay River, Firebag, and Surmont fields) and chemical tests were done for SAGD conditions (especially at the mature level), these new technologies and applications will be a guidance to the other types of steam operations (cyclic steam injection and steamflooding) using horizontal injectors and producers. In addition to the discussed studies and practices, a plethora of field-scale activities from the Middle East, far east Asia, and the Americas have been reported on consistently. Most of those are early-stage practices or pilots, but a few are related to mature heavy-oil recovery operations. Examples include Kuwait (data collection and development plans for new heavy-oil potentials), Oman (steam management surveillance in the Mukhaizna field), Brazil (development options for the offshore Atalanta field), Venezuela (ongoing operations in the Orinoco belt), Alaska (field-scale polymer-flooding test), China (practices in the Liaohe and Bohai Bay fields), Canada (cold production using methane/ propane mixture and electrical heating pilots in Alberta), Colombia (applications of autonomous inflow-control devices in the Rubiales field), and Indonesia (identification of rod-pump failures in the Duri field). Recommended additional reading at OnePetro: www.onepetro.org. SPE 196072 Laboratory and Field Testing of a Steam-Limiting Flow-Control Device Developed for Thermal Applications by Marty Lastiwka, Suncor Energy, et al. SPE 197321 Surveillance Approach of Steam Management in a Heavy-Oil Reservoir, Oman by Hajer Al Mahruqi, Occidental Petroleum SPE 198697 Effective Reservoir Management With Flow-Control Devices for SAGD Producer Wells in the Mackay River by Giuseppe Rosi, RGL Reservoir Management, et al.

Design and Analysis of a New Profile Control Tool: Swirling Autonomous Inflow-Control Device

Summary Edge/bottomwater cresting or even breaking into the wellbore has been a major factor affecting crude-oil production and has not been overcome so far. Aiming at this problem, this paper designs a new autonomous inflow-control device (AICD) profile control tool—swirling AICD—on the basis of the research of profile control tools used in the past. The AICD is mainly based on the principle of automatic phase separation, the splitting of three-way pipes, and the principle of vortex depressurization. Combined with the special flow path, the production of edge/bottomwater can be effectively restrained. Computational fluid dynamics (CFD) numerical simulation and indoor flow experiments are used to prove the water-control function of the swirling AICD, to obtain the pressure and velocity distribution of fluid flow in the AICD, and to obtain the influencing factors and their influence rules. Based on these analyses, we established the swirling AICD mathematical model, which has laid a theoretical foundation for the application of swirling AICDs in wells.

Modelling the reservoir-to-tubing pressure drop imposed by multiple autonomous inflow control devices installed in a single completion joint in a horizontal well

Autonomous inflow control devices (AICDs) are used to introduce an additional pressure drop between the reservoir and the tubing of a production well that depends on the fluid phase flowing into the device: a larger pressure drop is introduced when unwanted phases such as water or gas enter the AICD. The additional pressure drop is typically represented in reservoir simulation models using empirical relationships fitted to experimental data for a single AICD. This approach may not be correct if each completion joint is equipped with multiple AICDs as the flow at different AICDs may be different. We use high-resolution numerical modelling to determine the total additional pressure drop introduced by two AICDs installed in a single completion joint in a horizontal well. The model captures the multiphase flow of oil and water through the inner annulus into each AICD. We explore a number of relevant oil-water inflow scenarios with different flow rates and water cuts. Our results show that if only one AICD is installed, the additional pressure drop is consistent with the experimentalzly-derived empirical formulation. However, if two AICDs are present, there is a significant discrepancy between the additional pressure drop predicted by the simulator and the empirical relationship. This discrepancy occurs because each AICD has a different total and individual phase flow rate, and the final steady-state flow results from a self-organising mechanism emerging from the system. We report the discrepancy as a water cut-dependent correction to the empirical equation, which can be used in reservoir simulation models to better capture the pressure drop across a single completion containing two AICDs. Our findings highlight the importance of understanding how AICDs modify flow into production wells, and have important consequences for improving the representation of advanced wells in reservoir simulation models.

Study Assesses Incentives, Development Strategies for Peruvian Mature Heavy Oil

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 196217, “Assessment of Government Incentives and Development Strategies To Revitalize Mature Heavy-Oil Fields in the Peruvian Jungle,” by Nosser A. Jurado, SPE, National Bank Financial, and Victor A. Huerta, SPE, Universidad Nacional de IngenerÍ​​​​​​​a, prepared for the 2019 SPE Annual Technical Conference and Exhibition, Calgary, 30 September–2 October. The paper has not been peer reviewed. Mature heavy-oil fields in the northern Peruvian jungle have produced oil for more than 40 years under primary recovery mechanisms (cold methods). The complete paper explores technical and economic development options to produce heavy-oil resources at commercial rates and showcases three optimization scenarios of higher recovery efficiency aimed at increasing net present value at the basin level. Introduction The constant decline of medium- and light-oil production in most Peruvian fields in recent years, along with the increase in domestic demand, indicates that innovative redevelopment strategies should be implemented for recent large heavy-oil discoveries in the Marañon Basin. The Norperuano pipeline in its current condition and egress capacity allows exploitation of proved developed producing volumes of Blocks 64, 192, 8, and 95 but constrains the commerciality and development possibilities for Block 67 (Piraña, Dorado, and Paiche fields) and Block 64 (Situche field), which jointly could pro-duce up to 70,000 B/D between 2027 and 2029. The main issue is the present constraint for transportation and blending of heavy oil and diluents. Therefore, an infrastructure revamp is necessary. The authors believe that capital expenditure (CAPEX) to carry out these improvements and expansions is necessary and must be addressed between the operators in the area and the Peruvian government while considering all social and current environmental issues. Analysis of Production Performance and Recovery Most Peruvian heavy-oil fields have been discovered in the Marañon Basin. Production history indicates a strong water-drive mechanism by which oil production declines as water rate increases, while reservoir pressure is sustained with a less than 20% pressure decrease. Generally speaking, Marañon wells have been drilled following slant trajectories and are only completed with slotted liners without a selective completion. Consequently, no method exists to isolate water zones or encroachment, and oil productivity and relative permeability to oil decrease rapidly as water cut increases. Horizontal wells have been proposed for the Bretaña heavy-oil field in Block 95. This field is similar to the Jibaro and Jibarito fields in Block 192, with completions featuring autonomous inflow-control devices (AICDs) to delay water breakthrough while improving production performance and increasing oil recovery. Another alternative suggested to increase recovery factor and prevent water breakthrough is dual completion with electrical submersible pumps (ESPs). This completion type has been envisioned for Block 192. On a well-by-well basis, increasing the recovery factor by implementing new technologies is possible. On a transportation-and-gathering basis, however, issues remain in the basin. A production deferment of at least 7% has been the result of several factors, including a lack of appropriate well-service programs to replace ESPs and clean boreholes, inadequate infrastructure, deteriorating roads accessing the fields, the lack of a supply-change-management program, and a lack of appropriate management of social and environmental issues. CAPEX allocations to the Norperuano pipeline would minimize this problem at the basin level and might solve delay issues at the field level for all blocks.

Horizontal Infill Well With AICDs Improves Production in Mature Field

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 195450, “Horizontal Infill Well With AICDs Improves Production in Mature Field: A Case Study,” by Ilhami Giden, SPE, and Michael Nirtl, SPE, OMV Austria; Hans Thomas Maier, SPE, University of Leoben; and Ismarullizam Mohd Ismail, SPE, Tendeka, prepared for the 2019 SPE Europec featured at the 81st EAGE Annual Conference and Exhibition, London, 3–6 June. The paper has not been peer reviewed. This paper compares the performance of three mature-field horizontal infill wells, one of which is completed with autonomous inflow-control devices (AICDs). Two of the horizontal infill wells are targeting attic oil in an area with low risk of gas production; one of these two wells is completed with slotted liners and the other with AICDs. The third horizontal well was placed in an area with higher gas saturation. The AICDs were found to choke back a high amount of fluid and keep the water cut at a stable plateau•level. Field Introduction Matzen is a supermature oil field northeast of Vienna and is one of the largest onshore oil fields in Europe. The field consists of several stacked reservoirs, of which the 16th Tortonian horizon (16.TH) is the largest. The westernmost part of the 16.TH is called the Bockfliess area. In this area, 77 wells are currently active: 62 are production wells and 15 are injection wells. During 2011 to 2015, the last major field-redevelopment project in the area, with the objective of doubling the gross production rate, was executed. One goal of the project included a conversion from low-rate sucker rod pumps (SRPs) to high-rate electrical submersible pumps (ESPs). Horizontal infill wells were also drilled to optimize the ultimate recovery in the reservoir. The 16.TH sandstone reservoir lies between –1490 and –1455 m TVDss [total vertical depth subsea (i.e., total vertical depth minus the elevation above mean sea level of the depth reference point of the well)], with excellent permeability and an average porosity of 27%. Reservoir temperature•is 60°C and current reservoir pressure is 120 bar. Oil gravity is 25•°API, while oil viscosity is 5•cp. Average water cut exceeds 97%. AICD Technology In recent years, several different types of AICDs have been designed. The most common device types are fluidic-diode, electrical-resistivity, and rate-controlled-production (RCP). This paper covers the RCP type. The working principle of RCP AICDs differs from type to type. The Levitating-Disc AICD. The AICD that is installed in Well BO 208 is an improved version of the RCP. The design works on the principle of a levitating disc. The AICD valve restricts the flow rate of low-viscosity fluids. When gas or water flows through the AICD valve at the same drawdown, the velocity of the water and gas will increase, reducing the dynamic pressure and levitating the disc toward the inlet to choke the flow. The AICD valve is assembled as part of the sand-screen joint. The reservoir fluids enter the completion through the sand-screen filter and flow into the in-flow-control housing where the AICD is mounted. The fluids then flow into the production stream to the surface together with the production from the rest of the screens.

Analytical, numerical and experimental study of gas coning on horizontal wells

Nowadays, new horizontal wells prone to experience gas cone problem usually have multiple production zones. These wells are equipped with inflow control devices (ICDs) or autonomous inflow control devices (AICDs) to mitigate the production of the undesired fluid. In the proposed study, we use analytical calculation, numerical simulations and experimental results to analyze different production strategies when using long horizontal wells in such reservoirs. By the end, we first identified numerical models to represent the dynamic behavior of a gas–oil interface. By validating them through an analytical solution, we used an active control strategy both to obtain and to analyze the associated flow rate for different positions of the interface in steady state from static equilibrium to the well neighborhood. The findings of this research reaffirm there is no strategy that overcomes the production with critical flow rate in steady state. However, the exact critical flow rate is a theoretical value, being hard to assess in the field. In this way, the main contribution of this study is to indicate for the case in consideration the usual production strategy of using multiple zones equipped with AICDs, since it has a cumulative production extremely close to the theoretical maximum and it represents a well-known technology for field applications.

Structural Parameter Optimization and Performance Analysis of Autonomous Inflow Control Device

The Autonomous Inflow Control Device (AICD) adjusts the inflow of the horizontal wellbore by adding additional resistance to the fluid, thereby prolonging the water seepage time and enhancing oil recovery. The performance of AICD mainly depends on structural parameters. The computational fluid dynamics software is used to analyze the influence of structural parameters on the performance of AICD. The results show that the diameter of the variable diameter section, the diameter of the restrictor and the diameter of the outlet are the main factors affecting the performance of the inflow control device. The fluid parameter sensitivity simulation results show that the oil phase viscosity and water content have a great influence on the performance of AICD, while the influence of oil phase density on the performance of the device is negligible; the pressure drop under the pure water condition of this type of AICD is more than twice that of pure oil condition, so it has better water control ability.

Combining Passive and Autonomous Inflow-Control Devices in a Trilateral Horizontal Well in the Alvheim Field

Summary In this paper we describe the analysis, test, and design work to deliver an optimal lower completion for a trilateral well by integrating passive and autonomous inflow-control devices (ICDs) (AICDs) at the Alvheim Field offshore Norway. In 2015, both passive ICDs and AICDs were tested in the laboratory with Alvheim fluids at reservoir conditions. The experimental flow testing demonstrated that the AICD chokes gas more efficiently than the passive ICD. The experimental results enabled correct modeling of AICDs in both the reservoir-simulation model and the simpler steady-state inflow model. The following lower-completion strategy was established for the new well: Where the well was close to the overlying gas cap, AICDs should be used, whereas passive ICDs with variable strength were to be used elsewhere to optimize the inflow. During the drilling phase, the steady-state model was updated with the as-drilled information; the lower-completion design for each branch focused on obtaining what was estimated to be an optimal inflow depending on the oil volume per drainage area. A key uncertainty in the design work was whether shaly zones along the wellbore would creep/collapse with time and act effectively as packers. The lower completion covered 7 km of reservoir penetration in the three branches, and 15 unique oil tracers were installed to evaluate the cleanup and the inflow profile along the well. The well started producing in May 2016 and a successful cleanup was confirmed by oil-tracer responses. In August 2016, a restart-tracer-sampling campaign was performed after a 12-day shut-in, and this formed the basis for a “chemical production log.” The tracer-based inflow interpretation was compared quantitatively with the model-predicted inflow and qualitatively to the tracer responses seen during the cleanup. The comparison confirmed that the lower completion works as initially planned. The interpretation further indicated that the upper zone has a lower degree of pressure support than the lower zone, and that the larger shaly sections have creeped/collapsed and act as packers. The well has exceeded predrill production expectations, with an average oil rate of 3375 std m3/d (21,240 STB/D) during the first production year. A large part of exceeding the predrill expectations is attributed to the lower-completion design, where the focus has been to optimize such that the whole well contributes, from the heel to all toes.

Technology Focus: Production and Facilities (December 2018)

Technology Focus Creativity and innovation have long characterized production and facilities, and this year is no exception. Much of the work reported this past year was conducted during the recent period of low oil prices. The economic challenges of the oil industry clearly have provided a strong stimulus for even more creativity and innovation. The use of big data and analytics appeared in a number of papers with an emphasis on the use of artificial intelligence (AI) for building databases used to monitor the health of equipment and structure risk-based-inspection (RBI) strategies. Monitoring data inputs from thousands of sensors (paper OTC 28990) allows an AI application to predict an impending failure and notify operators by text or email when the incipient problem is detected so that proactive maintenance can be scheduled to avoid an unplanned shutdown or catastrophic failure. This strategy is being successfully applied to compressors but no doubt will be used to monitor other high-cost, critical service equipment as well (paper SPE 188803). Progress continues on the design and application of inflow-control devices (ICDs). Introduced only a few years ago, these devices are still in a rapid development stage for both design and application. Now, ICDs are applied successfully to improve the fluid-injection patterns for both steamfloods and waterfloods, the latter being described as a successful field application (paper SPE 189824). For steamfloods, passive and autonomous ICD designs were evaluated and their performance modeled using computational fluid dynamics (paper SPE 189721). The integration of subsurface modeling and surface-facility design by the development of a data-driven stochastic work flow (paper SPE 187462) demonstrated a means to reduce both subsurface and facility costs by reducing the biases that inevitably come into play during the generation of a field-development plan. Other innovative work was reported on field optimization, the prediction of asphaltene precipitation, and the integration of RBI with vibration-induced fatigue failure of installed piping systems. Interesting work not discussed here includes evaluating corrosion under severe conditions and the development of an oil-droplet-coalescing pump for use in water treatment. Recommended additional reading at OnePetro: www.onepetro.org. SPE 188803 Machines Performance Algorithmic Modeling for Anticipating Machines Health Using Real-Time Condition-Monitoring Data by W. Almadhoun, ADMA-OPCO, et al. SPE 189721 Evaluation of Inflow-Control-Device Performance Using Computational Fluid Dynamics by M. Miersma, University of Alberta, et al. SPE 187256 Production Optimization of Shenzi Field in the Deepwater Gulf of Mexico by P. Ashton, BHP, et al. SPE 190149 A Diagnostic Approach To Predict Asphaltene Deposition in Reservoir and Wellbore by Davud Davudov, University of Oklahoma, et al. OTC 28352 Integrating an RBI Approach for Vibration-Induced Fatigue Into a Mechanical-Integrity Program by Paul Crowther, Wood, et al.

Reservoir simulator-friendly model of fluid-selective, downhole flow control completion performance

Wells with long production/injection intervals (e.g. horizontal or multi-lateral wells) can be equipped with flow control completion (FCC), which allows zonal control of in/out-flow and is a proven method to improve sweep efficiency, extend well life, and reduce the production volumes of unwanted fluids. The application of FCC is essential to development of many oil fields with complex geology, uncertain reservoir description, close to contact completions or unfavourable mobility ratio.FCC technology keeps developing, for instance the recently introduced Autonomous Inflow Control Device (AICD) or Valve (AICV) strongly reacts to unwanted phases (gas or water) restricting their flow in-situ, which improves recovery as well as reduces the volume of unwanted fluids and the production uncertainty.This paper presents a novel approach to incorporate into a reservoir simulator the flow performance of a downhole flow control completion equipped with flow control devices discriminating flowing fluids, e.g. reacting to water/gas flow distinctly differently than to oil. AICDs and AICVs are examples of such devices. The novel approach is verified by numerical simulation and is further compared against the traditional modelling approach on a reservoir model.In the case of oil and water/gas flow, the multi-modal response of the device is new in the industry, and the reservoir simulators are not yet up-to-date to model such performance. The segregated flow in the annulus results in the device(s) reacting sequentially to either oil or water/gas, as opposed to the “homogeneous flow” modelling approach that is traditionally assumed in reservoir simulators. Capturing the sequential reaction of the device to either oil or water/gas in a reservoir simulator is challenging. The equations derived here solve this problem, and offer a more accurate way of modelling autonomous flow control completion performance in a commercial reservoir simulator.This work is an important contribution to the advanced well completion technology modelling and evaluation. This technology is likely to define the future of advanced wells.

Technology Focus: Heavy Oil (March 2018)

Technology Focus Despite the recent downturn, a significant number of pilot- or demonstration-scale applications of existing technologies to develop new heavy-oil fields or new technologies to develop existing fields have been reported over the past year. I have selected two of them (SPE 184974 and SPE 184154) in this issue. While they might be projects that started a few years ago when oil prices were at a peak level, they are interesting and still relevant because the projects have continued and valuable results and observations have been shared. Reported cases of cost-effective applications such as well stimulation using chemicals and solvents have also been prominent over the past few years. Well-based applications such as stimulation or production optimization (SPE 184094) are quite useful to improve the productivity in smaller fields. On the other hand, efforts on cost reduction in large-scale thermal projects were obvious. Yet, in laboratory-scale experimental investigations, observations on the use of nanoparticles (SPE 184117) and new- generation chemicals to improve the efficiency of large-scale thermal and non-thermal (mainly chemical flooding) applications are very promising. I also would like to mention high-tech imaging applications to map the heat distribution in field-scale applications (SPE 184971). The areas listed seem to be the trend of new research studies and field applications along with optimization attempts on the basis of data-driven modeling. The focus will also be on new technology attempts toward the reduction of the cost of heavy-oil production, including lower-cost (solar panels) and in-situ steam generation (SPE 184118), minimizing steam needs by use of chemical additives and solvents (solvent-aided thermal—steam or electromagnetic—processes), and nonthermal applications (well stimulation by chemicals and solvents). I hope to read more papers in the coming years on the philosophical approaches to describing the problems and limitations of existing solutions because complex heavy-oil applications still need more effort on model development and experimental data generation. I included SPE 185633 in this issue as a good example of this kind of attempt. Recommended additional reading at OnePetro: www.onepetro.org. SPE 184118 In-Situ Steam Generation: A New Technology Application for Heavy-Oil Production by Ayman R. Al-Nakhli, Saudi Aramco, et al. SPE 184117 Experimental Study for Enhancing Heavy-Oil Recovery by Nanofluid Followed by Steam Flooding NFSF by Osamah Alomair, Kuwait University, et al. SPE 184094 Fluidic-Diode Autonomous Inflow-Control Device for Heavy-Oil Application by Georgina Corona, Halliburton, et al. SPE 184971 Satellite Monitoring of Cyclic Steam Stimulation Without Corner Reflectors by Michael D. Henschel, MDA, et al.