Effect of systematic and random flow measurement errors on history matching: a case study on oil and wet gas reservoirs

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Abstract

History matching is the process of modifying a numerical model (representing a reservoir) in the light of observed production data. In the oil and gas industry, production data are employed during a history matching exercise in order to reduce the uncertainty in associated reservoir models. However, production data, normally measured using commercial flowmeters that may or may not be accurate depending on factors such as maintenance schedules, or estimated using mathematical equations, inevitably has inherent errors. In other words, the data which are used to reduce the uncertainty of the model may have considerable uncertainty in itself. This problem is exacerbated for gas condensate and wet gas reservoirs as there are even greater errors associated with measuring small fractions of liquid. The influence of this uncertainty in the production data on history matching has not been addressed in the literature so far. In this paper, the effect of systematic and random flow measurement errors on history matching is investigated. Initially, 14 production data sets with different ranges of systematic and random errors, from 0 to 10%, have been employed in a history matching exercise for an oil reservoir and the results have later been evaluated based on a reference model. Subsequently, 23 data sets with errors ranging from 0 to 20% have been employed in the same process for a wet gas reservoir. The results show that for both cases systematic errors considerably affect history matching, while the effect of random errors on the considered scenarios is seen to be insignificant. Although reservoir model parameters in the wet gas reservoir were not as sensitive to the flow measurement errors as in the oil reservoir, for both cases, the future production forecast was significantly affected by the errors. Permeability was seen to be the most sensitive history matching parameter to the flow measurement errors in the oil reservoir, while for the wet gas reservoir, the most sensitive parameter was the forecast of future oil and gas production. Finally, considering the noticeable effect of systematic errors on both cases, it is suggested that flowmeter calibration and regular maintenance is prioritised, although the subsequent economic cost needs to be considered.
Original languageEnglish
Pages (from-to)2853-2862
Number of pages10
JournalJournal of Petroleum Exploration and Production Technology
Volume9
Issue number4
Early online date19 Apr 2019
DOIs
Publication statusPublished - 1 Dec 2019

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Flow measurement
Measurement errors
History
Gases
Systematic errors
Random errors
Flowmeters
Gas condensates
Gas industry
Oils
Numerical models
Calibration
Economics
Uncertainty
Liquids
Costs

Bibliographical note

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Keywords

  • Flow measurement
  • History matching
  • Systematic error
  • Random error
  • Wet gas reservoir

ASJC Scopus subject areas

  • Energy(all)
  • Engineering(all)

Cite this

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title = "Effect of systematic and random flow measurement errors on history matching: a case study on oil and wet gas reservoirs",
abstract = "History matching is the process of modifying a numerical model (representing a reservoir) in the light of observed production data. In the oil and gas industry, production data are employed during a history matching exercise in order to reduce the uncertainty in associated reservoir models. However, production data, normally measured using commercial flowmeters that may or may not be accurate depending on factors such as maintenance schedules, or estimated using mathematical equations, inevitably has inherent errors. In other words, the data which are used to reduce the uncertainty of the model may have considerable uncertainty in itself. This problem is exacerbated for gas condensate and wet gas reservoirs as there are even greater errors associated with measuring small fractions of liquid. The influence of this uncertainty in the production data on history matching has not been addressed in the literature so far. In this paper, the effect of systematic and random flow measurement errors on history matching is investigated. Initially, 14 production data sets with different ranges of systematic and random errors, from 0 to 10{\%}, have been employed in a history matching exercise for an oil reservoir and the results have later been evaluated based on a reference model. Subsequently, 23 data sets with errors ranging from 0 to 20{\%} have been employed in the same process for a wet gas reservoir. The results show that for both cases systematic errors considerably affect history matching, while the effect of random errors on the considered scenarios is seen to be insignificant. Although reservoir model parameters in the wet gas reservoir were not as sensitive to the flow measurement errors as in the oil reservoir, for both cases, the future production forecast was significantly affected by the errors. Permeability was seen to be the most sensitive history matching parameter to the flow measurement errors in the oil reservoir, while for the wet gas reservoir, the most sensitive parameter was the forecast of future oil and gas production. Finally, considering the noticeable effect of systematic errors on both cases, it is suggested that flowmeter calibration and regular maintenance is prioritised, although the subsequent economic cost needs to be considered.",
keywords = "Flow measurement, History matching, Systematic error, Random error, Wet gas reservoir",
author = "Mahdi Sadri and Shariatipour, {Seyed M.} and Andrew Hunt and Masoud Ahmadinia",
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