January 2023

Optimizing oil production while achieving net zero ambitions with advanced completions

Autonomous inflow control technology could provide the key to enhance oil production from produced water treatment operations, while significantly reducing emissions. A recent study has shown that advanced completions could help the industry safely and sustainably accelerate net zero ambitions.
Mojtaba Moradi / Tendeka

By its nature, the oil and gas industry has the resourcefulness and resilience to eliminate unnecessary carbon emissions. However, traditional development plans have relied on the application of conventional wells, with minimal or no emphasis on the well completion. This produces a mixture of oil and other, often unwanted fluids, such as water and/or gas, and it requires a costly, energy-intensive separation process at the surface.  

The result is excessive and unnecessary GHGs being emitted into the atmosphere. While the process has been optimized to some extent, with unwanted fluids often re-injected back to the reservoir, it is now widely recognized and accepted as one of the greatest challenges facing the industry in its drive toward net zero delivery of energy. 

Rate-controlled production (RCP) autonomous inflow control devices (AICDs), self-regulating devices—based on the properties of the fluid passing through—have been applied successfully in numerous light and heavy oil wells to greatly reduce the production of excessive, unwanted water and gas. The fully interchangeable device, field-adjustable and engineered for a wide variety of applications, negates the need for costly treatment at the surface and preferentially chokes unwanted produced fluids, while allowing oil production from the entire length of the well. The design and deployment of such devices vary widely, as do their application in injection and production wells, as well as different types of reservoirs.  

Several operators have reported a significant reduction of up to 60% in water treatment requirements while optimizing oil production. Consequently, this has markedly lowered greenhouse gas (GHG) emissions.  

A study by Tendeka, a TAQA company, utilized both a workflow methodology and a publicly available GHG footprint estimator to illustrate the significant impact of its FloSure AICD, Fig. 1. This was to reduce GHG emissions on two typical oil fields—onshore, cold heavy oil productions, and light oil, highly productive offshore wells.1  

Fig. 1. AICD completion. Image: Tendeka.
Fig. 1. AICD completion. Image: Tendeka.

The performance of each development, in terms of GHG emissions and energy consumption, was evaluated with, and without, the autonomous completions, when a fixed volume of oil production for each field is assumed. 


Across oilfield developments, flow control devices are proven to optimize the performance of both injection and production wells. Much like the function of a standard ICD, the AICD was designed to balance the influx of reservoir fluids in production wells, by proactively delaying the production of unwanted fluids before breakthrough. However, once a breakthrough occurs, the AICD works to autonomously limit undesired materials with lower viscosity, such as gas and water, from entering production wells.  

Injection wells are used to either store the unwanted fluids or reinject them to improve oil recovery from production wells. AICDs have been designed specifically to optimize the performance of injection wells by improving the injection conformance, thereby reducing injection cost, improving field NPV and boosting the reliability of injection well systems. 

As shown in Fig. 2, the AICD is normally assembled as part of the sand screen joint, if required. The flow path from the reservoir is marked by blue arrows. The fluids from the reservoir enter the completion through the sand screen jackets and move into the AICD housing, where the device is mounted. The fluids then flow through the device and into the production fluid conduit and flow to the surface. Figure 3 illustrates the components of the FloSure AICD device.  

Fig. 2. An AICD unit mounted into sand screen joints. Image: Tendeka
Fig. 2. An AICD unit mounted into sand screen joints. Image: Tendeka
Fig. 3. The design and operating principle of FloSure AICD. Image: Tendeka
Fig. 3. The design and operating principle of FloSure AICD. Image: Tendeka

As shown above, fluids from the reservoir enter the device through an orifice in the top plate, impacting the levitating disk and dispersing radially between the disk and the top plate, before the fluids turn around the edge of the disk to leave through the ports at the bottom of the device. The degree of flow restriction is a result of the position of the levitating disk, while the disk position is determined by the balance of three principal forces:  

  1. A change in momentum force 
  1. A force created by the frictional pressure drop of the fluid flowing through the device 
  1. A lifting force, similar to the force created on an aeroplane wing, as a result of the pressure variations along a streamline, as described by Bernoulli's equation. 

Figure 4 shows the AICD performance curve for various fluids under single-phase conditions. The pressure drops experienced by fluid flowing through the AICD is a function of the volumetric flow rate and the viscosity and density of the fluid. 

Fig. 4. AICD performance prediction for single-phase oil, water and gas. Image: Tendeka
Fig. 4. AICD performance prediction for single-phase oil, water and gas. Image: Tendeka


The production of unwanted fluids has been an inherent challenge for the oil and gas industry. Not only do they lower oil production efficiency, they are also associated with other unavoidable problems, including well integrity and limitation on the capacity of surface processing facilities. The treatment and re-injection of fluids back to the reservoir further compounds the costs and consequences associated with GHG emissions and energy consumption. AICDs are a proven technology to control unwanted fluids in the ground and mitigate economic and environmental issues. 

From exploration to the production stage, the GHG footprint estimator predicts the amount of GHG emitted from any individual operation, process and treatment. This calculation enables the operator to recognize the major GHG emitter activities and use novel and enhanced technologies, methods and/or workflows to optimize the process toward achieving net zero. 

Tendeka’s investigation carried out a comparison, in terms of GHG emissions and energy consumption, between two typical oilfield developments—with and without an AICD completion—when a fixed volume of oil production for each field is assumed: 

  • Field A is onshore with cold, heavy oil production and an API of 23 
  • Field B is a highly productive offshore well, with light oil and an API of 35  

The calculation was performed, using an algorithm developed by Stanford University. The parameters assumed in the study are shown in Table 1 for both fields. The gas composition was assumed as N2, CO2, C1, C2, C3, C4+ and H2S, with mole fractions of 2, 4, 86, 4, 2, 1 and 1 respectively. No flaring was permitted for all fields. Several other parameters were assumed throughout the study. 


Field A: AICD to control water production. High-viscosity fields pose several challenges, including production of a high volume of water. Oil is often left behind, and wells usually operate at a high water cut—up to 99%—even during the early days of production. The application of AICDs has helped to reduce the amount of water production for many wells across the world.2  

As Table 2 shows, the amount of GHG emissions and energy consumption could be significantly reduced by the deployment of AICDs (67% and 82% respectively), compared to non-AICD wells for this example. Figures 5a and 5b show the GHG emissions contribution from each operation involved in oil production for both scenarios. The data suggest that production and surface processing are the major factors. 

Fig. 5a and 5b. GHG emission contribution from various operations—Field A. Image: Tendeka
Fig. 5a and 5b. GHG emission contribution from various operations—Field A. Image: Tendeka

Table 3 provides the contributions of these two operations in both total GHG emissions and energy consumption. 

Field B: AICD to control gas and water production. Highly productive offshore wells usually suffer from production of a high volume of gas and often excessive water production, which would lower oil production. If they are not equipped for AICD completions, this could result in choking back the wells. However, results from numerous applications have proved the success of applying AICDs to reduce gas-oil ratio (GOR) and water cut (WC) in such fields.3 Lowering GHG emissions, while delivering a fixed volume of oil from these wells, could eventually result in a reduction in the required number of wells, as shown in Table 1. 

As Table 2 shows, the amount of GHG emissions and energy consumption in Field B could also be significantly reduced by the deployment of AICDs (26% and 30%, respectively), compared to non-AICD wells. Table 3 summarizes the contribution of production and surface processing operations in both GHG emissions and energy consumption. Again, these operations are the major contributors to GHG emissions. In this case, the surface processing facility is the highest contributor, with a share of about 78% and 90% respectively, in wells with and without AICDs.  


Growing energy demand, intensified by the fallout of Covid-19, conflict in Ukraine, and pressure to tackle climate change, has seen the oil and gas industry hasten the adoption of smarter and more sustainable technologies, to secure supply and cut costs and emissions. Advanced well completions, using sophisticated autonomous flow control technologies, have already shifted the paradigm for many global operators. 

The study by Tendeka, utilizing a workflow methodology and a publicly available GHG footprint estimator, has shown that the use of AICDs minimizes the production of unwanted fluids in two different oilfield developments. The results could radically reduce requirements of the energy-intensive treatment process and prove that advanced completion could help the industry to achieve net zero targets while optimizing oil production. 


  1. El-Houjeiri, H. M., and A. R. Brandt, “Oil Production Greenhouse gas emissions estimator (OPGEE) User guide & Technical documentation,” Department of Energy Resources Engineering, Stanford University, 2022. Available at: [OPGEE: GHG Emissions Estimator] 
  1. “Production optimisation of heavy oil reservoirs using autonomous inflow control devices,SPE paper 193718, SPE International Heavy Oil Conference and Exhibition, Kuwait, 2018. https://doi.org/10.2118/193718-MS. 
  1. “Enhanced oil production with autonomous inflow control devices (AICD) in an oil rim reservoir Malaysia,” OTC paper 30363-MS, Offshore Technology Conference 2020. https://doi.org/10.4043/30363-MS. 
About the Authors
Mojtaba Moradi
Mojtaba Moradi is a Subsurface manager at Tendeka in Aberdeen. He holds a PhD (2016) in petroleum engineering from Heriot-Watt University. He is a member of the European Association of Geoscientists and Engineers (EAGE), and SPE.
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