Live Well Models a Tool for Production Optimization

Rachapudi, R. V.; Haider, Bader Y.A.; Al-Mutairi, Talal; Deyain, Khaled Waleed Al; Al-Yahya, M..; Shakeel, Ahmed Anjum; Qureshey, K. R.; Harith, Mikhail

doi:10.2118/167469-ms

Day 3 Wed, October 30, 2013 2013

DOI: 10.2118/167469-ms

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Live Well Models a Tool for Production Optimization

R. V. Rachapudi

Bader Y.A. Haider

Talal Al-Mutairi

et al.

Abstract: Continuous well performance monitoring plays a key role in making decision related to well workover and production optimization. Well parameters and corresponding rates over a period of time will represent the change in well performance. Live Well models are useful for estimating the continuous well production rates. Well models become live if they get updated with changing fluid and reservoir properties along with proper calibration to latest well conditions.In general industry practice is to update the model… Show more

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Cited by 3 publications

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Integrated Production Testing Framework to Improve Next Generation Production Workflows

Rao

David

2015

Day 3 Wed, November 11, 2015

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Production Test data is a critical parameter for several production operations and reservoir management workflow. High quality Production test data is vital for better understanding of the flow behavior and rates to ensure optimized production and maximize the asset value. Current Production Testing practice in oil industry includes separator testing or MPFM at well heads or at degassing station. However, the frequency of testing varies between one to three months for each well which may not sufficient to realize the full potential of Digital Oil Field (DOF) workflows. Virtual Flow Metering (VFM) technique along with well model results shall provide continuous well rates that would significantly improve the quality of decisions made through the production workflow. This brings in a varied Production testing environment for different well categories and types. In order to continuously provide the real time production parameters to the DOF workflows, it is essential to integrate the different Production testing techniques through an Integrated Production Testing Framework. In this paper, the authors discuss an Integrated Production Testing Framework that comprise of validated real time and historical data, integrated workflows and the enabling technologies that includes calibrated well models, trained neural network models and visualization tools. Production test data obtained using traditional methods (PTS) and MPFM will be at low to medium frequency. VFM using neural network model estimates the flow rates continuously between the actual tests at a high frequency. This framework is suitable for production, injection wells that are installed with MPFM, PTS, water cut meters and covers different production testing scenarios Like PLT, ESP testing, Long-term MRT and step rate injectivity testing. The framework enables implementation of continuous estimated rates, exception based alarms, automatic well test validation, track well test operations, guidance for reservoir monitoring program, KPI monitoring, precise back allocation leading to better production optimization and reservoir management across oil and gas producing assets. This paper discusses an integrated approach to manage different Production testing methodologies to streamline the usage of the data for different workflows..

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Integrated Production Testing Framework to Improve Next Generation Production Workflows

Rao

David

2015

Day 3 Wed, November 11, 2015

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Real-Time Production Surveillance and Optimization at a Mature Subsea Asset

Borden

Porto

et al. 2016

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A real-time production surveillance and optimization system has been developed to integrate available surveillance data with the objective of driving routine production optimization. The system aims to streamline data capture, automate data quality assurance, integrate high and low frequency data to extract maximum value, optimize the design and analysis of commingled well tests, and provide real-time multi-phase well rate estimates for continuous well performance evaluation. A key challenge identified was the need to understand individual well contribution during commingled well tests, as traditional approaches may provide unrepresentative results. Additionally, the well tests are typically infrequent, thus further limiting the reliability of estimated well rates as production system dynamics between well tests are not accounted for. A third challenge recognized was the need for efficient testing procedures in order to minimize deferred production. To address these issues, a fully integrated model of the production system was used, and is driven by a computational algorithm that automatically calibrates the model to real-time sensor data. A new systematic approach was developed to analyze multi-segment commingled well tests simultaneously to improve the accuracy of resulting measurements. Between well tests, a robust regression algorithm is used to continuously adapt and re-calibrate the model when well conditions change. This algorithm can automatically detect sensor bias and apply an appropriate weighting when calibrating the model. In addition, a regularization technique is also used to prevent physically unrealistic changes in the well parameters between infrequent well tests. The technology is currently applied to an offshore deepwater asset and early benefits include a 2% production uplift realized from optimizing gas lift allocation and performing a single well routing change recommended by the technology. Furthermore, more reliable rate allocation to wells has improved the quality of subsurface models used for reservoir management.

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Commingled Well Test Analysis (CWTA) and its Application to Assess Health of Multiphase Flow Meters (MPFM) for Deep Water Conventional Assets

Patra

Kedia

Gollu

et al. 2022

Day 3 Wed, November 02, 2022

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Historically well production flow surveillance has been attracting attention from reservoir engineers. The accurate estimation of individual well contribution, Has profound impact on reservoir management. Often production allocation suffers from multiple issues such as quality of available production data and production rate estimation in case of inaccurate and uneconomical measurements. These issues can be mitigated if the well has accurate, calibrated Multiphase Flow Meters (MPFMs) and Virtual Flow Meters (VFMs). Reliability of digital meters is primarily dependent on regular well testing to keep the model updated and tuned to latest reservoir characteristics. As an industry wide common practice, well tests are performed in a timely manner to ensure to allocate production accurately to each well. But performing solo well tests for subsea wells is not trivial as it may seem. Differed production due to downtime associated with flowing subsea wells to a test separator and inability of mature wells to flow to the test separator result in additional challenges. Under such situations, commingled well tests are performed to estimate well rates. Individual well rates can be estimated using test by difference (TBD) method. The apparent simplicity of the TBD method often results in incorrect estimation of allocation rates as the test conditions and production conditions differs significantly. As a result, the credibility of the forecast and the ability to optimize production are compromised. In this paper a novel application called Commingled Well Test Analysis (CWTA) is reviewed which addresses these aforementioned issues. This integrated application comprises of data loading interface, data visualization interface, core optimization engine and an interactive user interface. To demonstrate the capability, three wells from a deep water conventional wells are analyzed using commingled well tests and well performance parameters (PI, WCUT and GOR) are obtained. Based on the tuned parameters, well rates are predicted and compared against rates obtained from sales meter and MPFM meters. As per the comparison, well allocation rates are validated and health of MPFM meters are assessed. As an additional benefit, proper designing of commingled well tests enable in 25-30% time savings of well testing.

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Live Well Models a Tool for Production Optimization

Cited by 3 publications

References 4 publications

Integrated Production Testing Framework to Improve Next Generation Production Workflows

Integrated Production Testing Framework to Improve Next Generation Production Workflows

Real-Time Production Surveillance and Optimization at a Mature Subsea Asset

Commingled Well Test Analysis (CWTA) and its Application to Assess Health of Multiphase Flow Meters (MPFM) for Deep Water Conventional Assets

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