Production Optimization Techniques For Multi-Well Artificial Lift Study

1989 ◽  
Author(s):  
R.J. Steele ◽  
R.W. Hallsky
Keyword(s):  
Optimization Techniques ◽  
Production Optimization ◽  
Artificial Lift

First Digital Intelligent Artificial Lift Production Optimization Technology in UAE Dual-String Gas Lift Well - Business Case and Implementation Plan

2019 ◽  
Author(s):  
Ahmed Alshmakhy ◽  
Khadija Al Daghar ◽  
Sameer Punnapala ◽  
Shamma AlShehhi ◽  
Abdel Ben Amara ◽  
...  
Keyword(s):  
Business Case ◽  
Production Optimization ◽  
Implementation Plan ◽  
Artificial Lift ◽  
Gas Lift

Production Optimization over 20% with Artificial Lift ESP Pilot Systems in Mature Oil Field, Case Study from Middle East

2014 ◽  
Author(s):  
Hector Aguilar ◽  
Aref Almarzooqi ◽  
Tarek Mohamed El Sonbaty ◽  
Leigber Villarreal
Keyword(s):  
Middle East ◽  
Production Optimization ◽  
Oil Field ◽  
Field Case ◽  
Artificial Lift

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.

Service Industry & University Collaboration in Teaching Production Optimization with Artificial Lift

2014 ◽  
Author(s):  
Rajan N Chokshi ◽  
William C Lane ◽  
Shari Dunn-Norman ◽  
Chatetha Chumkratoke
Keyword(s):  
Service Industry ◽  
Production Optimization ◽  
Artificial Lift

scholarly journals Significant production improvement using optimization of completion and artificial lift: case studies from South-West Iran

2020 ◽  
Author(s):  
Rahman Ashena ◽  
Mahmood Bataee ◽  
Hamed Jafarpour ◽  
Hamid Abbasi ◽  
Anatoly Zolotukhin ◽  
...  
Keyword(s):  
Case Studies ◽  
Gas Injection ◽  
Field Tests ◽  
Production Optimization ◽  
South West ◽  
Artificial Lift ◽  
Production Improvement ◽  
Artificial Gas Lift ◽  
Gas Lift ◽  
Standard Gas

AbstractProductivity of wells in South-West Iran has decreased due to completion and production problems in recent decades. This is a large risk against sustainable production from the fields. To allow stable production, an important measure is completion and production optimization including artificial lift methods. This was investigated using simulations validated by pilot field tests. Several case studies were considered in terms of their completion and production. Five scenarios were investigated: natural production through annulus and tubing (scenario-1 and 2), artificial gas lift production through annulus (scenario-3), through tubing using non-standard gas lift (scenario-4) and using standard gas lift (scenario-5). Scenario-1 is currently the case in most wells of the field. To find the optimal scenario and completion/production parameters, simulations of 11 wells of an oilfield in the region were carried out using nodal and sensitivity analysis. The optimized parameters include wellhead pressures (WHPs), tubing dimensions, maximum tolerable water cuts and gas oil ratios and artificial gas injection rate. Simulation results were validated by pilot field tests. In addition, appropriately selected wellhead and Christmas trees for all scenarios were depicted. Simulations confirmed by field pilot tests showed that optimization of completion and production mode and parameters can contribute largely to production improvement. The results showed that the current scenario-1 is the worst of all. However, production through tubing (scenario-2) is optimal for wells which can produce with natural reservoir pressure, with an increase of 800 STB/Day rate per well compared with scenario-1. However, for wells requiring artificial gas lift, the average production rate increase (per well) from the annulus to tubing production was 1185 STB/Day. Next, using the standard gas lift (scenario-5) was found to be the optimal mode of gas lifting and is strongly recommended. WHPs in scenario-5 were the greatest of all, whereas scenario-1 gave the lowest WHPs. The optimal tubing diameter and length were determined. The greatest maximum tolerable water cut was obtained using scenario-5, whereas the lowest was with scenario-1. The maximum tolerable GOR was around 1900 scf/STB. Changing of scenarios did not have significant effect on maximum tolerable GOR. The optimal artificial gas injection rates were found. This validated simulation work proved that completion and production optimization of mode and parameters had considerable contribution to production improvement in South-West Iran. This sequential comprehensive work can be applied in any other field or region.

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.

Sign in / Sign up

Export Citation Format

Share Document