Integrated Production Optimization And Surface Facilities Management Through Advanced Optimization Techniques

2012 ◽  
Author(s):  
Giorgio Viadana ◽  
Danilo Albani ◽  
Marco Nicola Distaso ◽  
Almatasem Sharon
Keyword(s):  
Optimization Techniques ◽  
Production Optimization ◽  
Facilities Management ◽  
Integrated Production

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goal, that we have faced were:All facilities were designed for early production stage in late 1980's, and as the asset outdated the pipeline sizes, routing and compression strategies needs review.Detecting, predicting and reducing liquid loading is required so that the operator can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.

Production Optimization – Integrated Production Modeling – El Portón Oilfield

2005 ◽  
Author(s):  
P. Marin ◽  
V. Lattanzi ◽  
J.G. Rodriguez ◽  
C. Canel ◽  
C. Gilardone
Keyword(s):  
Production Optimization ◽  
Integrated Production ◽  
Production Modeling

scholarly journals Stochastic Simplex Approximate Gradient for Robust Life-Cycle Production Optimization: Applied to Brugge Field

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
Bailian Chen ◽  
Jianchun Xu
Keyword(s):  
Life Cycle ◽  
Net Present Value ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Optimization Techniques ◽  
Production Optimization ◽  
Operating Conditions ◽  
Optimization Under Uncertainty ◽  
Theoretical Argument ◽  
Gas Industry

In oil and gas industry, production optimization is a viable technique to maximize the recovery or the net present value (NPV). Robust optimization is one type of production optimization techniques where the geological uncertainty of reservoir is considered. When well operating conditions, e.g., well flow rates settings of inflow control valves and bottom-hole pressures, are the optimization variables, ensemble-based optimization (EnOpt) is the most popular ensemble-based algorithm for the robust life-cycle production optimization. Recently, a superior algorithm, stochastic simplex approximate gradient (StoSAG), was proposed. Fonseca and co-workers (2016, A Stochastic Simplex Approximate Gradient (StoSAG) for Optimization Under Uncertainty, Int. J. Numer. Methods Eng., 109(13), pp. 1756–1776) provided a theoretical argument on the superiority of StoSAG over EnOpt. However, it has not drawn significant attention in the reservoir optimization community. The purpose of this study is to provide a refined theoretical discussion on why StoSAG is generally superior to EnOpt and to provide a reasonable example (Brugge field) where StoSAG generates estimates of optimal well operating conditions that give a life-cycle NPV significantly higher than the NPV obtained from EnOpt.

Integrated surface facilities management: Continuous Production Optimization

2014 ◽  
Author(s):  
Andrea Di Sarra ◽  
Sara Scaramellini ◽  
Paolo Cerri ◽  
Simone Pellegrini ◽  
Giorgio Viadana ◽  
...  
Keyword(s):  
Continuous Production ◽  
Production Optimization ◽  
Facilities Management

Front-End Integrated Production System Modelling for Production Optimization – Experience from a Niger Delta Field

2021 ◽  
Author(s):  
Felix Okoro ◽  
Elias Arochukwu ◽  
Segun Adomokhai ◽  
Linda Dennar
Keyword(s):  
Production System ◽  
Flow Line ◽  
Integrated System ◽  
Production Optimization ◽  
System Modelling ◽  
Total Production ◽  
Integrated Production ◽  
Head Pressure ◽  
Line Pressure ◽  
Year 2000

Abstract The M001 project involved the hook-up of 12 wells (17 conduits) which were drilled and completed between year 2000 and 2005 but were closed-in for operational reasons, until year 2019 when the first seven (7) conduits on cluster MX1 were cleaned up successfully. The seven conduits (Well-A, Well-B, Well-C, Well-D, Well-E, Well-F & Well-G) were expected to flow via three 8" bulk lines. Post well open-up and handover to production, significant bulking / backing out effects were observed. An average Flow Line Pressure (FLP) of ∼22 bar was recorded on the flowlines, hence limiting the capacity to bulk the wells, [FLP increases towards Flowing Tubing Head Pressure (FTHP) hence, pushing the well out of the critical flow envelope as FTHP<<1.7FLP]. Due to this challenge, total production from Cluster MX1 was sub-optimal with only five (5) conduits out of seven (7) able to flow due to bulking and backing out effect. The sub-optimal performance from the conduits were investigated using the Integrated Production System Model (IPSM) / PIPESIM models. Four different scenarios were run in the model and the calibrated IPSM model indicated all 7 conduits should flow if there are no surface restrictions. The model identified pressure, mass and rate imbalances in the integrated system and suggested the presence of a restriction at the manifold, causing sub-optimal production from the wells. The model outcome triggered an onsite investigation / troubleshooting from the wellhead to the manifold at the facilities end where an adjustable choke was identified in the ligaments of the manifold. In line with process safety requirements, a risk assessment was carried out and a Management of Change (MOC) raised to remove the adjustable choke at the manifold. Post implementation of the intervention, all the seven (7) conduits produced without any bulking effect. Total production realized from the seven (7) conduits post execution of the recommended action is ca. 9.3 kbopd against 5.2 kbopd pre-intervention. A total of ca. 4.1 kbopd production gain was realized and 10 mln USD proposed for additional bulkline was saved.

Unifying of Steady State and Transient Simulations Methodologies for Increasing Oil Production of Integrated Network of Wells, Pipeline and Topside Processing Equipment

2021 ◽  
Author(s):  
Zalina Ali ◽  
Astriyana Anuar ◽  
Nicolas Grippo ◽  
Nurshahrily Emalin Ramli ◽  
Najmi Rahim
Keyword(s):  
Steady State ◽  
System Optimization ◽  
Integrated System ◽  
Production Optimization ◽  
Full Potential ◽  
Production Network ◽  
Network Modelling ◽  
Integrated Network ◽  
Transient Phenomena ◽  
Integrated Production

Abstract Aging facilities and increasing complexity in operations (e.g., increasing water cut, slugging, sand or wax production) continue to widen the gap between actual production and the full potential of the field. To enable production optimization scenarios within an integrated system comprises of reservoirs, wells and surface facilities, the application of an integrated network modelling has been applied. The highlight of this paper is the synergy of Integrated Production Network Modelling (IPNM) utilizing Steady State Simulator (PROSPER-GAP) and the Transient Simulator (OLGA) tools to identify potential quick gains through gaslift optimization as well as mid and long-term system optimization alternatives. The synergy enables significant reduction in transient simulation time and reduced challenges in OLGA well matching, especially in selecting accurate modelling parameters e.g., well inflow performance (validated well (string) production data, reservoir pressure, temperature and fluid properties and the Absolute Open Flow (AOF) of each well). The paper showcased the successful production gain achieved as well as the workflows and methodologies applied for both Steady State Integrated Production Modelling (IPM Steady State) and Integrated Transient Network Modelling (IPM Transient) as tools for production enhancement. Even though IPM Steady State shows promising results in term of field optimization potential, to increase accuracy and reduce uncertainties, IPM Transient is recommended to be performed to mimic the actual transient phenomena happening in the well to facilities

Hierarchical Multiscale Methods for Life-Cycle-Production Optimization: A Field Case Study

SPE Journal ◽  
2015 ◽  
Vol 20 (05) ◽  
pp. 896-907 ◽  
Author(s):  
D. F. Oliveira ◽  
A. C. Reynolds
Keyword(s):  
Net Present Value ◽  
Simple Procedure ◽  
Optimization Techniques ◽  
Multiscale Methods ◽  
Production Optimization ◽  
Real Field ◽  
Historical Period ◽  
Reference Case ◽  
Multiscale Optimization ◽  
Hierarchical Multiscale

Summary We apply hierarchical multiscale techniques previously developed by the authors to estimate the well controls that maximize the net present value of the long-term production from a real field offshore Brazil. This field has been in production for several years, and it represents a significant share of the overall oil production for the country. The production-optimization step is preceded by a 10-year historical period, where seismic and production data were history matched by use of ensemble-based approaches. The well controls on a sequence of control steps (time intervals) are optimized for the next 10 years of production by use of the hierarchical-multiscale-optimization and the refinement-indicator-based hierarchical-multiscale-optimization techniques, which refine the control steps as the optimization proceeds. The performance of our approaches is compared with that of a reference case, which applies the well rates used to forecast the production of the real field, as well as with the performance of a standard optimization procedure that uses a fixed set of well controls and a simple procedure to refine control steps.

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