All-Electric Intelligent Completion System: Evolution of Smart Completion

2021 ◽  
Author(s):  
Orient Balbir Samuel ◽  
Ashvin Avalani Chandrakant ◽  
Fairus Azwardy Salleh ◽  
Ahsan Jamil ◽  
Zulkifli Ibrahim ◽  
...  
Keyword(s):  
Phase 1 ◽  
Cost Optimization ◽  
Control Valve ◽  
Production Optimization ◽  
Economic Life ◽  
Control Line ◽  
Flow Control Valve ◽  
Efficient System ◽  
Associated Gas ◽  
Field Development

Abstract Field D is a mature offshore field located in East Malaysia. A geologically complex field having multiple-stacked reservoirs with lateral and vertical faulted compartments & uncertainty in reservoir connectivity posed a great challenge to improve recovery from the field. Severe pressure depletion below bubble point and unconstrained production from gas cap had contributed to premature shut-ins of more than 50% of strings. As of Dec 2019, the field has produced at a RF less than 20%. Initial wells design consisted of conventional dual strings & straddle packers with sliding sleeves (SSD). Field development team was challenged for a revamp on completion design to enhance economic life of the depleting field. In 2015, as part of Phase-1 development campaign, nine wells including four water injectors were completed initiating secondary recovery through water flood. An approach of Smart completion comprising of permanent downhole monitoring system (PDHMS) and hydraulic controlled downhole chokes or commonly known as flow control valve (FCV) was adopted in all the wells in order to optimize recovery from the field and step towards intervention-less solutions. Seeing the benefits of intelligent completion in Phase-1, Phase-2, drilled and completed in 2019 – 2020 has been equipped with new technology "All-electric Intelligent Completion System" in 4 out of 8 oil producers. The new design addresses the reservoir complexity, formation pressure and production challenges and substantial cost optimization, phasing out the load of high OPEX to CAPEX. Installation of "All-electric Intelligent Completion System" has proven to be an efficient system compared to hydraulic smart completions system. It requires 50% to 75% less installation time per zone and downhole FCV shifting time is less than five minutes compared to several hours full cycle for hydraulic system. The new system has capability to complete up to 27 zones per well with single cable. It gave more options and flexibility in order to selectively complete more zones compared to hydraulic FCVs which requires individual control line for each zone. Future behind casing opportunities (BCO) have been addressed upfront, saving millions of future investment on rig-less intervention. In addition to that, non-associated gas (NAG) zones have been completed to initiate in-situ gaslift as and when required avoiding the dependency on aging gaslift facility. The scope of the paper is to show case the well design evolution during Field D development and highlight on how smart completion has evolved from original dual completion to hydraulic smart and recently to electric smart system, how it has contributed to cost and production optimization during installation and production life and also support the gradual digitalization of the Field D. In the end it demonstrates the optimized completion design to enhance the overall economic life of the depleting field.

scholarly journals Binary Linear Programming as a Tool of Cost Optimization for a Water Supply Operator

2021 ◽  
Vol 13 (6) ◽  
pp. 3470
Author(s):  
Przemysław Kowalik ◽  
Magdalena Rzemieniak
Keyword(s):  
Linear Programming ◽  
Water Supply ◽  
Electric Power ◽  
Energy Savings ◽  
Cost Optimization ◽  
Production Optimization ◽  
Production Costs ◽  
Pump System ◽  
Power Cost ◽  
Binary Linear Programming

The problem of scheduling pumps is widely discussed in the literature in the context of improving energy efficiency, production costs, emissions, and reliability. In some studies, the authors analyze the available case studies and compare the results; others present their own computational methods. In the paper, a problem of pump scheduling in regular everyday operations of a water supply operator is considered. The issues of water production optimization and energy savings are part of the topic of sustainable development. The objective of the article is the minimization of the cost of electric power used by the pumps supplying water. It is achieved thanks to the variability of both the demand for water and the price of electric power during the day combined with the possibility of storing water. The formulation of an existing electric power cost optimization problem as a binary linear programming problem was improved. An essential extension of the above mathematical model, which enables more flexible management of the pump system, was also proposed. An example containing real-world input data was successfully solved using Microsoft Excel with a free OpenSolver add-in.

A Multi-modes Flow Control Valve for Simplifying the Driving System of Pneumatic Soft Robots

2020 ◽  
pp. 1-1
Author(s):  
Yang Yang ◽  
Yongjian Zhao ◽  
Songyi Zhong ◽  
Yan Peng ◽  
Yi Yang ◽  
...  
Keyword(s):  
Flow Control ◽  
Control Valve ◽  
Flow Control Valve ◽  
Soft Robots ◽  
Driving System

Pattern Recognition Approach to Fault Diagnosis in the DAMADICS Benchmark Flow Control Valve

2003 ◽  
Vol 36 (5) ◽  
pp. 861-866 ◽  
Author(s):  
A. Marciniak ◽  
C.D. Bocăială ◽  
R. Louro ◽  
J. Sa da Costa ◽  
J. Korbicz
Keyword(s):  
Pattern Recognition ◽  
Fault Diagnosis ◽  
Flow Control ◽  
Control Valve ◽  
Flow Control Valve ◽  
Pattern Recognition Approach

Production Optimization for Second Stage Field Development Using ICD and Advanced Well Placement Technology

2008 ◽  
Author(s):  
D. Maggs ◽  
A.G. Raffn ◽  
Francisco Porturas ◽  
J. Murison ◽  
F. Tay ◽  
...  
Keyword(s):  
Production Optimization ◽  
Well Placement ◽  
Field Development ◽  
Second Stage

Design and evaluation of orifice arrangement for particle-excitation flow control valve

2011 ◽  
Vol 171 (2) ◽  
pp. 283-291 ◽  
Author(s):  
Daisuke Hirooka ◽  
Koichi Suzumori ◽  
Takefumi Kanda
Keyword(s):  
Flow Control ◽  
Control Valve ◽  
Flow Control Valve

L1 Adaptive Control for Aircraft Air Management System Pressure-Regulating Bleed Valve

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
John Cooper ◽  
Chengyu Cao ◽  
Jiong Tang
Keyword(s):  
Management System ◽  
Control Valve ◽  
Pressure Control ◽  
Adaptive Controller ◽  
System Model ◽  
Flow Control Valve ◽  
L1 Adaptive Control ◽  
System Pressure ◽  
L1 Adaptive Controller ◽  
Linear Controllers

This paper presents an L1 adaptive controller for pressure control using an engine bleed valve in an aircraft air management system (AMS). The air management system is composed of two pressure-regulating bleed valves, a temperature control valve, a flow control valve, and a heat exchanger/precooler. Valve hysteresis due to backlash and dry friction is included in the system model. The nonlinearities involved in the system cause oscillations under linear controllers, which decrease component life. This paper is the unique in the consideration of these uncertainties for control design. This paper presents simulation results using the adaptive controller and compares them to those using a proportional–integral (PI) controller.

Design and Analysis of a Flow-Control Valve With Controllable Pressure Compensation Capability for Mobile Machinery

2021 ◽  
Author(s):  
Bo Wang ◽  
Yunwei Li ◽  
Long Quan ◽  
Lianpeng Xia
Keyword(s):  
Pressure Drop ◽  
Flow Control ◽  
Pressure Difference ◽  
Control Valve ◽  
Flow Control Valve ◽  
Continuous Control ◽  
Small Flow ◽  
Pressure Compensation ◽  
Force Compensation ◽  
Control Accuracy

Abstract There are the problems in the traditional pressure-compensation flow-control valve, such as low flow control accuracy, small flow control difficulty, and limited flow range. For this, a method of continuous control pressure drop Δprated (i.e. the pressure drop across the main throttling orifice) to control flow-control valve flow is proposed. The precise control of small flow is realized by reducing the pressure drop Δprated and the flow range is amplified by increasing pressure drop Δprated. At the same time, it can also compensate the flow force to improve the flow control accuracy by regulating the pressure drop Δprated. In the research, the flow-control valve with controllable pressure compensation capability (FVCP) was designed firstly and theoretically analyzed. Then the sub-model model of PPRV and the joint simulation model of the FVCP were established and verified through experiments. Finally, the continuous control characteristics of pressure drop Δprated, the flow characteristics, and flow force compensation were studied. The research results demonstrate that, compared with the traditional flow-control valve, the designed FVCP can adjust the compensation pressure difference in the range of 0∼3.4 MPa in real-time. And the flow rate can be altered within the range of 44%∼136% of the rated flow. By adjusting the compensation pressure difference to compensate the flow force, the flow control accuracy of the multi-way valve is improved, and the flow force compensation effect is obvious.

Artificial Intelligence Assisted Well Portfolio Optimization - An Automated Reservoir Management Advisory System to Maximize the Asset Value - Case Study from ADNOC Onshore

2021 ◽  
Author(s):  
Subba Ramarao Rachapudi Venkata ◽  
Nagaraju Reddicharla ◽  
Shamma Saeed Alshehhi ◽  
Indra Utama ◽  
Saber Mubarak Al Nuimi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Hybrid Approach ◽  
Simulation Models ◽  
Production Optimization ◽  
Added Value ◽  
Risk Scores ◽  
Well Performance ◽  
Field Development ◽  
Advisory System ◽  
Gas Lift

Abstract Matured hydrocarbon fields are continuously deteriorating and selection of well interventions turn into critical task with an objective of achieving higher business value. Time consuming simulation models and classical decision-making approach making it difficult to rapidly identify the best underperforming, potential rig and rig-less candidates. Therefore, the objective of this paper is to demonstrate the automated solution with data driven machine learning (ML) & AI assisted workflows to prioritize the intervention opportunities that can deliver higher sustainable oil rate and profitability. The solution consists of establishing a customized database using inputs from various sources including production & completion data, flat files and simulation models. Automation of Data gathering along with technical and economical calculations were implemented to overcome the repetitive and less added value tasks. Second layer of solution includes configuration of tailor-made workflows to conduct the analysis of well performance, logs, output from simulation models (static reservoir model, well models) along with historical events. Further these workflows were combination of current best practices of an integrated assessment of subsurface opportunities through analytical computations along with machine learning driven techniques for ranking the well intervention opportunities with consideration of complexity in implementation. The automated process outcome is a comprehensive list of future well intervention candidates like well conversion to gas lift, water shutoff, stimulation and nitrogen kick-off opportunities. The opportunity ranking is completed with AI assisted supported scoring system that takes input from technical, financial and implementation risk scores. In addition, intuitive dashboards are built and tailored with the involvement of management and engineering departments to track the opportunity maturation process. The advisory system has been implemented and tested in a giant mature field with over 300 wells. The solution identified more techno-economical feasible opportunities within hours instead of weeks or months with reduced risk of failure resulting into an improved economic success rate. The first set of opportunities under implementation and expected a gain of 2.5MM$ with in first one year and expected to have reoccurring gains in subsequent years. The ranked opportunities are incorporated into the business plan, RMP plans and drilling & workover schedule in accordance to field development targets. This advisory system helps in maximizing the profitability and minimizing CAPEX and OPEX. This further maximizes utilization of production optimization models by 30%. Currently the system was implemented in one of ADNOC Onshore field and expected to be scaled to other fields based on consistent value creation. A hybrid approach of physics and machine learning based solution led to the development of automated workflows to identify and rank the inactive strings, well conversion to gas lift candidates & underperforming candidates resulting into successful cost optimization and production gain.

Integrated Production Model as a Tool for Optimization the Development Strategy of the Sakhalin Oil and Gas Condensate Field

2021 ◽  
Author(s):  
Oleksandr Doroshenko ◽  
Miljenko Cimic ◽  
Nicholas Singh ◽  
Yevhen Machuzhak
Keyword(s):  
History Matching ◽  
Effective Field ◽  
Production Optimization ◽  
Production Model ◽  
Production Forecast ◽  
Hydrocarbon Production ◽  
Integrated Production ◽  
Wellhead Pressure ◽  
Field Development ◽  
The Impact

Abstract A fully integrated production model (IPM) has been implemented in the Sakhalin field to optimize hydrocarbons production and carried out effective field development. To achieve our goal in optimizing production, a strategy has been accurately executed to align the surface facilities upgrade with the production forecast. The main challenges to achieving the goal, that we have faced were:All facilities were designed for early production stage in late 1980's, and as the asset outdated the pipeline sizes, routing and compression strategies needs review.Detecting, predicting and reducing liquid loading is required so that the operator can proactively control the hydrocarbon production process.No integrated asset model exists to date. The most significant engineering tasks were solved by creating models of reservoirs, wells and surface network facility, and after history matching and connecting all the elements of the model into a single environment, it has been used for the different production forecast scenarios, taking into account the impact of infrastructure bottlenecks on production of each well. This paper describes in detail methodology applied to calculate optimal well control, wellhead pressure, pressure at the inlet of the booster compressor, as well as for improving surface flowlines capacity. Using the model, we determined the compressor capacity required for the next more than ten years and assessed the impact of pipeline upgrades on oil gas and condensate production. Using optimization algorithms, a realistic scenario was set and used as a basis for maximizing hydrocarbon production. Integrated production model (IPM) and production optimization provided to us several development scenarios to achieve target production at the lowest cost by eliminating infrastructure constraints.

Electric Motors Coupled to Hydraulic Motors as Actuators for Hydraulic Hardware-in-the-Loop Simulation

2005 ◽  
Author(s):  
Scott Driscoll ◽  
James D. Huggins ◽  
Wayne J. Book
Keyword(s):  
Complete System ◽  
Control Valve ◽  
Operating Conditions ◽  
Flow Control Valve ◽  
Hardware In The Loop ◽  
Hydraulic Systems ◽  
Advantages And Disadvantages ◽  
Hydraulic Motors ◽  
Proportional Flow ◽  
Hil Simulation

Hardware-in-the-Loop (HIL) Simulation enables testing of an actual physical component of a system under a variety of conditions without the expense of full scale testing. In hydraulic systems, flows or pressures that interface with the component in question are controlled by a computer running a simulation designed to emulate a complete system under real operating conditions. Typically, servo valves are used as actuators to control the flows or pressures. This paper investigates the use of electric servo-motors coupled to hydraulic gear motors as alternative actuators, and discusses some of the advantages and disadvantages that motors have in comparison to valves. A demonstration HIL simulation involving a mobile proportional flow control valve attached to an emulated backhoe is described, and results are compared to data from a real backhoe.

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