A nonlinear, adaptive observer for gas-lift wells operating under slowly varying reservoir pressure

Abstract Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorithm to tackle the challenging task of optimally allocating the gas lift injection rate through numerical modeling and simulation studies to maximize the oil production of a Middle Eastern oil field with 20 production wells with limited amount of gas to be injected. The key objective of this study is to assess the performance of the wells of the field after applying gas lift as an artificial lift method and applying the genetic algorithm as an optimization algorithm while comparing the results of the network to the case of artificially lifted wells by utilizing ESP pumps to the network and to have a more accurate view on the practicability of applying the gas lift optimization technique. The comparison is based on different measures and sensitivity studies, reservoir pressure, and water cut sensitivity analysis are applied to allow the assessment of the performance of the wells in the network throughout the life of the field. To have a full and insight view an economic study and comparison was applied in this study to estimate the benefits of applying the gas lift method and the GA optimization technique while comparing the results to the case of the ESP pumps and the case of naturally flowing wells. The gas lift technique proved to have the ability to enhance the production of the oil field and the optimization process showed quite an enhancement in the task of maximizing the oil production rate while using the same amount of gas to be injected in the each well, the sensitivity analysis showed that the gas lift method is comparable to the other artificial lift method and it have an upper hand in handling the reservoir pressure reduction, and economically CAPEX of the gas lift were calculated to be able to assess the time to reach a profitable income by comparing the results of OPEX of gas lift the technique showed a profitable income higher than the cases of naturally flowing wells and the ESP pumps lifted wells. Additionally, the paper illustrated the genetic algorithm (GA) optimization model in a way that allowed it to be followed as a guide for the task of optimizing the gas injection rate for a network with a large number of wells and limited amount of gas to be injected.

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A Robust Short-Term Oil Production under a Bow-Tie Uncertainty Set for the Gas Lift Performance Curve

SPE Journal ◽

10.2118/206740-pa ◽

2021 ◽

pp. 1-13

Author(s):

André Ramos ◽

Carlos Gamboa ◽

Davi Valladão ◽

Bernardo K. Pagnoncelli ◽

Tito Homem-de-Mello ◽

...

Keyword(s):

Deterministic Model ◽

Probability Distributions ◽

Real Data ◽

Production Test ◽

Reservoir Pressure ◽

Performance Curve ◽

Out Of Sample ◽

Uncertainty Set ◽

Gas Lift ◽

Bow Tie

Summary The method of continuous gas lift has been commonly used in the oil industry to enhance production. Existing optimization models consider an approximate performance curve anchored by production test data, often disregarding reservoir uncertainty. We propose a robust optimization model that jointly considers the most recent data and an uncertainty set for the reservoir pressure, a critical parameter that is usually not measured precisely. As a result, we obtain what we call a “bow-tie” uncertainty set for the performance curves, in which the performance uncertainty increases when we move away from the production test’s operational point. We test our model with real data from an offshore oil platform and compare it against a fully deterministic model. We show superior out-of-sample performance for the robust model under different probability distributions of the reservoir pressure.

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Integrated application of flow pattern map for long-term gas lift optimization: a case study of Well T in Indonesia

Journal of Petroleum Exploration and Production Technology ◽

10.1007/s13202-019-00821-3 ◽

2020 ◽

Vol 10 (4) ◽

pp. 1635-1641

Author(s):

Silvya Dewi Rahmawati ◽

Steven Chandra ◽

Prasandi Abdul Aziz ◽

Wijoyo Niti Daton ◽

Ardhi H. Lumban Gaol

Keyword(s):

Flow Pattern ◽

Mechanistic Modeling ◽

Reservoir Pressure ◽

New Approach ◽

Classic Problem ◽

Flow Pattern Map ◽

Time Changes ◽

Gas Lift

AbstractGas lift optimization has been a classic problem since its inception. The problem with currently practiced optimization, the gas lift performance curve (GLPC), was the sole requirement for exhaustive calculation that has to be performed every time changes to the reservoir are acknowledged. The approach of mechanistic modeling has been proven to be a powerful tool to complement the analysis of GLP curves, especially in complex, multi-well gas lift system. This publication offers a new approach in modeling the progression of flow pattern map (FPM) in case of reservoir pressure decline. The findings presented in this publication encourage the hypothesis that FPM can be used with minimum alteration should there be any changes in reservoir pressure.

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Achieving Operational Excellence for Gas Lift Modeling in High Angle Wells with Multidisiplinary Approach

Proc. Indon. Petrol. Assoc., Digital Technical Conference, 2020 ◽

10.29118/ipa20-e-280 ◽

2020 ◽

Author(s):

F. Sajjad

Keyword(s):

Flow Instability ◽

Productivity Index ◽

Flow Assurance ◽

Reservoir Pressure ◽

High Angle ◽

Daily Production ◽

Design Modification ◽

Velocity Changes ◽

Gas Lift ◽

Deviated Wells

High angle wells are compulsory in offshore fields. These types of wells require better understanding on flow assurance dynamics and better planning on well intervention to ensure their operational efficiency. It is important to note that several wells have been experiencing severe production decline even though the current reservoir pressure is still high. In order to have a comprehensive understanding on liquid fallback, a transient fluid flow approach has been employed to investigate multiphase flow during gas lift operations. The simulation presents a 3-dimensional, time-based output that can simulate liquid fallback or severe slugging in pipe as a function of pipe diameter, gas lift valve placement, injected gas rate, and reservoir pressure that can address the flow assurance dynamics. The results from this research can be developed as an additional technical consideration before designing a gas lift system in highly deviated wells. Consideration on the placement of gas lift valves are also paramount in these cases, mainly avoiding places with flow instability or regions with sudden velocity changes. Results from the study, combined with well based performance are then compiled as a general guidance for the contractor to design a gas lift system on the basis of reservoir parameters such as Productivity Index, liquid viscosity and density, well deviation and trajectory, and gas supply to ensure operational and design excellence on gas lift design for deviated wells. Transient based simulation improved completion and gas lift design modification in the Lima Field, where higher and stable liquid production from daily production monitoring resulted in less well intervention from these wells.

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