Production Optimization of Multi-Lateral Wells Using Passive Inflow Control Devices

Hembling, Drew; Berberian, Garo; Al-Mumen, Adib Abdulmohsen; Simonian, Sam; Salerno, Giovanni

doi:10.2523/iptc-14094-ms

Cited by 4 publications

(1 citation statement)

References 3 publications

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“…The industry has used well-centric workflows, which are based on either employing a commercial steady-state wellbore simulator e.g. NETool or evaluation of the static data near the wellbore such as permeability, to design these completions (Hembling et al, 2009, Das et al, 2012, Gavioli and Vicario, 2012, Al-Khelaiwi, 2013, Birchenko et al, 2011. However, they cannot be the best frequently used in such dynamic, flow system since the design which they are suggesting is based on the best performance of the completion at a particular time, often only valid over the short period, as addressed by (Ogunsanwo et al, 2011, Ostrowski et al, 2010, Al-Jasmi et al, 2013, Moradi et al, 2014, Jackson et al, 2013.…”

Section: Introductionmentioning

confidence: 99%

Novel Integrated Approach Simultaneously Optimising AFI Locations Plus Number and (A)ICD Sizes

Dowlatabad¹

2015

Europec 2015

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The optimal design of Advanced Well Completions (AWCs) is an important step in field development planning nowadays. However, determination of optimum design of (Autonomous) Inflow Control Devices [(A)ICDs] and their integration with Annular Flow Isolations (AFIs) in an advanced well completed across a heterogeneous reservoir is a challenge which has not been addressed properly yet. Most used, variable strength (A)ICD completion design, workflows by industry are based on trial and error evaluations of a static well-reservoir models. Several researchers also suggested relating the strengths of the devices to near wellbore static reservoir properties such as permeability of the encountering layers. Both of these approaches do not capture the dynamic interactions between the well and constantly changing reservoir conditions. Moreover, neglecting mutual dependency of AFI location and (A)ICD design in the traditionally step-by-step (A)ICD-AFI design workflows, may result in a design delivering low overall productivity throughout the field life.A novel, integrated (A)ICD-AFI completion design workflow is presented in this paper. The workflow simultaneously optimises (A)ICDs strengths and number plus locations of AFIs in the horizontal and/or multilateral wells based on field's production lifetime. The approach includes stochastic optimisation algorithm coupled with a reservoir simulator and an in-house completion design programming code. The code is developed to automatically generate various (A)ICD-AFI completion configurations required to determine the optimum completion design while honouring practical concerns and economics. A novel AFI modelling technique developed allows integration of AFIs in the optimisation process.The application of the new and the traditional workflows are illustrated using heterogeneous reservoir simulation models. A significant improvement in total oil production for the wells, designed by the new workflow, was achieved comparing with the wells designed by the traditional workflows. The study aims to help well engineers in designing optimal advanced well completion delivering maximum possible field's added-value.

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Section: Introductionmentioning

confidence: 99%

Novel Integrated Approach Simultaneously Optimising AFI Locations Plus Number and (A)ICD Sizes

Dowlatabad¹

2015

Europec 2015

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Coupling Reservoir and Well Completion Simulators for Intelligent Multi-Lateral Wells: Part 1

et al. 2013

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To maximize well productivity and reservoir oil recovery in mature fields, advanced lateral designs with intelligent completions have been implemented during the last decade. The technology has been broadly applied, but how to effectively include its impact in reservoir well modeling is still being studied and developed. This paper describes an all-in-one system that combines nodal analysis and numerical simulation models to calculate the effect of intelligent completion components—such as swell packers, internal control valves (ICV), and inflow control devices (ICD)—on lateral production profiles. In complex and high heterogeneity reservoirs, single wells are economically unsustainable in the long term because of many factors, including reservoir properties, early water/gas breakthrough, and non-selective-layer flow control or preference flow zones. The use of multi-lateral wells (ML) enables maximum reservoir contact while different zones are produced at the same time. Moreover, for those cases in which reservoir pressure and heterogeneity between completions are significantly different, downhole devices can control early water breakthrough and provide hydro-dynamic equilibrium in more than one lateral. In this work, we used a 3D grid, multiphase flow and non-isothermal reservoir numerical simulator for advanced well design, and a wellbore nodal analysis simulator that numerically solves the partial differential equations between porous medium and the wellbore. When modeling the effect of any completion (ICD, ICV, and swell packers) on reservoir performance, the numerical simulator is coupled with a steady-state, network-based simulator that handles the completion effect inside the wellbore architecture. This study is determining how to optimize the intelligent-completion design in a Middle East field to evaluate the completion efficiency and production performance over time. The new coupled approach—believed to be an industry first for multi-laterals—is being used to model openhole and ICD-ICV completions and production forecasting in a multi-layered formation associated with an active aquifer.

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Production Optimization Through Utilization of Smart Wells in Intelligent Fields

Ranjith

Suhag

Balaji

et al. 2017

SPE Western Regional Meeting

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With improvements in technology and increasing amount of opportunities in more challenging assets, the use of smart well technologies to improve recovery has caught significant attention in the oil and gas industry in the last decade. Several workflows have been developed and proposed in order to automate the whole process that integrates several subprocesses focusing on specific parts of the surface or subsurface phenomena. Reservoir sweep is a crucial part of recovery efficiency, especially where significant investment is done by means of installing smart wells that feature inflow control valves (ICVs), which are remotely controllable. However, as it is a relatively newer concept, effective use of this technology has been a challenge. In this study, the objective is to present the efficient use of ICVs in intelligent fields to maximize sweep, and thus, recovery tied to the objective function. A standard realistic SPE reservoir simulation model of a waterflood process has been used where the smart well ICVs are controlled with conditional statements, called procedures, in a fully-commercial full-physics numerical reservoir simulator. Key performance indicators, including but not limited to water cut and oil rate, are used to adjust the degree of opening of ICVs on the producer side to balance injection on the injector side. This turns out to be a complex phenomenon of higher degree of nonlinearity in a multi-well system in a large field where several wells interact with each other. Objective function seeks to maximize the net present value (NPV) of cumulative oil recovery. Smart well technologies have been challenged with the associated cost component, thus, it is important to present the benefits of this technology with applications on more diverse cases showcasing different workflows. It has been observed that robust reservoir management in an intelligent field can significantly improve the sweep and recovery by utilization of smart wells with ICVs. The results are presented in a comparative way against the base case to illustrate the incremental value of use of ICVs, along with key performance indicators. Most importantly, it has been shown that the use of smart wells without a robust reservoir management strategy does not always lead to successful results. In reservoir management, it is not only important to catch the well level details but also to see the big picture at field level for improving reservoir performance beyond individual well performances, taking into account the interference between wells. Although smart wells with ICVs have been deployed on wells all over the field, unfortunately, some similar studies mainly focus on individual or near-wellbore performance rather than the whole asset. In this study, a field-wide approach is followed that integrates data from key performance indicators in an integrated workflow, which outlines efficient integration of variables available to optimize recovery.

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Production Optimization of Multi-Lateral Wells Using Passive Inflow Control Devices

Cited by 4 publications

References 3 publications

Novel Integrated Approach Simultaneously Optimising AFI Locations Plus Number and (A)ICD Sizes

Novel Integrated Approach Simultaneously Optimising AFI Locations Plus Number and (A)ICD Sizes

Coupling Reservoir and Well Completion Simulators for Intelligent Multi-Lateral Wells: Part 1

Production Optimization Through Utilization of Smart Wells in Intelligent Fields

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