Reservoir Management with Real-Time and Periodic Surveillance Data

Kabir, C.S.; Ismadi, Danu; Fountain, Sandra R.

doi:10.2118/132967-ms

Cited by 6 publications

(1 citation statement)

References 32 publications

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“…Applications of real-time data on intelligent wells have been widely documented in literature (Ong et al, 2009;Adeyemo et al, 2009;Goggins et al, 2009). Examples of utilizing the real time data to understand the reservoir are plenty in literature (Kabir et al, 2010;Kragas et al, 2004;Horne, 2007) The importance of rate allocation from a field rate to individual wells for hydrocarbon and water can be underestimated without identifying its potential negative ramifications. A less quality allocation could diminish or over state the benefits from production optimization or workover efforts.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Production Allocation in Intelligent Wells via Application of Models and Real-Time Surveillance Data

Wu¹,

Humphrey²,

Liao³

2012

All Days

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The accuracy and precision of well rates are paramount in reservoir management, well performance surveillance, flow assurance, and any third party processing arrangements. Rate allocation is traditionally based on well rate tests and downtime. This method is usually time-consuming and thus performed relatively infrequently. This could be inadequate for proactive asset management especially with wells that may produce in transient state.This paper discusses methodology to improve well rate allocation quality and save engineering time. In practice, many fields face some or all of the following challenges that are related to well rate allocation: 1) reservoir communication, 2) well interference, 3) changing skin factors or other near wellbore boundaries, 4) uncertainties around reservoir fluid properties, and 5) difficulty in obtaining well rate tests for a variety of reasons. For many intelligent wells, it is a common practice to install permanent downhole gauges which are playing critical roles in field management. This paper describes a framework on how to capitalize on the real time data from well pressure and temperature sensors and use the data in Integrated Asset Modeling (IAM) to allocate the well rate with enhanced accuracy, increased frequency, and reduced processing time.The paper uses Atlantis in Gulf of Mexico as an example to demonstrate this process. The real-time data supported model based allocation process becomes virtual flow meters for the intelligent wells. For Atlantis, field-wide allocation accuracy has been improved from previously +/-10% error using the traditional allocation method based on well rate test and downtime method to current +/-3% error using the new method. This paper also shows model maintenance is a journey that needs strenuous attention especially after water injections commences and more production wells come online.

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Section: Introductionmentioning

confidence: 99%

Enhancing Production Allocation in Intelligent Wells via Application of Models and Real-Time Surveillance Data

Wu¹,

Humphrey²,

Liao³

2012

All Days

View full text Add to dashboard Cite

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The Use of Combined Static and Dynamic Material-Balance Methods in Gas Reservoirs

Ismadi

Kabir

Hasan

2011

SPE Asia Pacific Oil and Gas Conference and Exhibition

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Estimating in-place volume associated with each well, leading to estimation of total reservoir in-place volume, is the cornerstone to any reservoir-management practice. Yet conventional methods do not always lend themselves for routine applications, particularly when used in singular fashion. However, combining them on the same plot has considerable merit in that they converge to the same solution when material-balance-derived average-reservoir pressure is used. This study presents a systematic procedure for estimating the initial gas in-place volume (GIIP) when real-time surveillance data of pressure, rate, and temperature are available at the wellhead. Specifically, we show that log-log diagnosis, followed by combined static- and dynamic-material-balance analysis, and transient-productivity-index (transient-PI) analysis lead to consistent solutions. Thermodynamic behavior of fluids is also explored to ensure that the converted pressures at the bottomhole and measured rates have consistency and accuracy for reservoir-engineering calculations. Layered systems were selected for this study because they represent most situations. Two synthetic cases probed issues pertaining to average-reservoir pressure computation with the pseudosteady-state (PSS) approach, and two field examples validated the approach presented here.

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Improved Understanding of Reservoir Connectivity in an Evolving Waterflood with Surveillance Data

Parekh

Kabir

2011

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Establishing connectivity among various injectors and producers is a key to improving the understanding of a reservoir under waterflood. This understanding improves the estimates for ultimate recovery and also helps to better define the future development plan. In deepwater turbidite reservoirs, numerical flow-simulation models are used to make performance predictions, with reservoir connectivity as one of the key uncertainties. In the initial phase of field development, interwell tracers were used to assess the connectivity. As more wells were drilled, updates were required for the simulation models. Instead of waiting for the next phase of an ongoing tracer program, both rate-transient analysis (RTA) and capacitance-resistance model (CRM) were used to understand connectivity. The input for both RTA and CRM are the rates and pressures, which are being gathered with real-time surveillance. This paper presents a case study to compare findings from the use of interwell tracer data with the results of CRM based on dynamic data. Another study element demonstrates the use of RTA in identifying and estimating the volume of thief zone. Attempts are made to use CRM and RTA to predict connectivity based on performance prior to experiencing water breakthrough. These case studies demonstrate the application of RTA and CRM in ongoing waterfloods. The CRM concurred with the initial tracer results and helped to understand the change in pressure distribution with time as the field was being developed. We learned that the use of CRM can be a viable alternative to an interwell tracer program to reduce uncertainty related to injector-producer connectivity. CRM also helped in understanding the efficiency of the injectors, which is important in a facility with limited water injection capacity. The ease of use of CRM and RTA makes them useful as screening tools in the process of developing a detailed flow-simulation model.

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Reservoir Management with Real-Time and Periodic Surveillance Data

Cited by 6 publications

References 32 publications

Enhancing Production Allocation in Intelligent Wells via Application of Models and Real-Time Surveillance Data

Enhancing Production Allocation in Intelligent Wells via Application of Models and Real-Time Surveillance Data

The Use of Combined Static and Dynamic Material-Balance Methods in Gas Reservoirs

Improved Understanding of Reservoir Connectivity in an Evolving Waterflood with Surveillance Data

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