Sensitivity to Initial Data Errors in Interpreting Temperature Logging of an Isolated Injection Well Segment

This study considers the inverse problems inherent in interpreting temperature logging data from an isolated segment of the injection well in order to ascertain its operating period and the thermophysical properties of the oil reservoir.The forward problem of thermal conductivity was reduced to a on...

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Main Authors: K. A. Potashev, D. R. Salimyanova, A. B. Mazo, A. A. Davletshin, A. V. Kosterin
Format: Article
Language:English
Published: Kazan Federal University 2024-07-01
Series:Учёные записки Казанского университета: Серия Физико-математические науки
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Online Access:https://uzakufismat.elpub.ru/jour/article/view/72
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author K. A. Potashev
D. R. Salimyanova
A. B. Mazo
A. A. Davletshin
A. V. Kosterin
author_facet K. A. Potashev
D. R. Salimyanova
A. B. Mazo
A. A. Davletshin
A. V. Kosterin
author_sort K. A. Potashev
collection DOAJ
description This study considers the inverse problems inherent in interpreting temperature logging data from an isolated segment of the injection well in order to ascertain its operating period and the thermophysical properties of the oil reservoir.The forward problem of thermal conductivity was reduced to a one-dimensional axisymmetric formulation within the oil reservoir layer, disregarding the vertical thermal exchange with neighboring layers.The inverse problem of determining the well operating period was solved by reformulating the forward problem with regard to the temperature field derivative, which enabled the use of first-order optimization methods. Thus, Nesterov’s method was applied. An algorithm to automatically scale one of the method’s parameters (step length) was developed, and the optimal value of the second parameter (inertial step) was calculated. This increased the efficiency of the method by 10 – 15 % in solving the problem under consideration.The algorithm’s stability against perturbations in the initial data on temperature and thermophysical properties was demonstrated. The sensitivity analysis revealed that a 1 % error in the temperature measurements results in a standard deviation of the solution, which is about 2 % from the true value of the well operating period. A similar level of error was seen when the thermal diffusivity was overor underestimated by approximately 15 %. The solution was little sensitive to variations in the heat transfer coefficient between the oil reservoir and the well at characteristic magnitudes; even with a twofold distortion, the error in the determination of the well operating period did not exceed 1.5 %. To mitigate the error in thermometry interpretation to 1 %, temperature measurements must have an error margin of no more than 0.25 %, alongside precisely specified thermophysical properties of the oil reservoir, or, alternatively, when temperature is measured accurately, the rock thermal diffusivity must be set within an error margin of less than 3 %, but it is nearly impossible under real conditions.Increasing the number of temperature measurements diminishes the sensitivity to measurement errors, with the optimal efficacy achieved at 10 measurements, rendering further increments impractical.Therefore, the algorithm’s stability and the solution’s sensitivity of the inverse problem of determining the reservoir thermal diffusivity for a given operating period of the well relative to temperature measurement errors were found. The results show that a 1 % error in temperature measurements leads to a standard deviation of about 6 % from the true value.
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institution Kabale University
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publishDate 2024-07-01
publisher Kazan Federal University
record_format Article
series Учёные записки Казанского университета: Серия Физико-математические науки
spelling doaj-art-0f7ef221f77d4e5cb26c8996c0b563412025-02-02T23:06:08ZengKazan Federal UniversityУчёные записки Казанского университета: Серия Физико-математические науки2541-77462500-21982024-07-01166223824910.26907/2541-7746.2024.2.238-24946Sensitivity to Initial Data Errors in Interpreting Temperature Logging of an Isolated Injection Well SegmentK. A. Potashev0D. R. Salimyanova1A. B. Mazo2A. A. Davletshin3A. V. Kosterin4Kazan Federal UniversityNational Research Centre “Kurchatov Institute”Kazan Federal UniversityOOO NPP “Chernyi Klyuch”Kazan Federal UniversityThis study considers the inverse problems inherent in interpreting temperature logging data from an isolated segment of the injection well in order to ascertain its operating period and the thermophysical properties of the oil reservoir.The forward problem of thermal conductivity was reduced to a one-dimensional axisymmetric formulation within the oil reservoir layer, disregarding the vertical thermal exchange with neighboring layers.The inverse problem of determining the well operating period was solved by reformulating the forward problem with regard to the temperature field derivative, which enabled the use of first-order optimization methods. Thus, Nesterov’s method was applied. An algorithm to automatically scale one of the method’s parameters (step length) was developed, and the optimal value of the second parameter (inertial step) was calculated. This increased the efficiency of the method by 10 – 15 % in solving the problem under consideration.The algorithm’s stability against perturbations in the initial data on temperature and thermophysical properties was demonstrated. The sensitivity analysis revealed that a 1 % error in the temperature measurements results in a standard deviation of the solution, which is about 2 % from the true value of the well operating period. A similar level of error was seen when the thermal diffusivity was overor underestimated by approximately 15 %. The solution was little sensitive to variations in the heat transfer coefficient between the oil reservoir and the well at characteristic magnitudes; even with a twofold distortion, the error in the determination of the well operating period did not exceed 1.5 %. To mitigate the error in thermometry interpretation to 1 %, temperature measurements must have an error margin of no more than 0.25 %, alongside precisely specified thermophysical properties of the oil reservoir, or, alternatively, when temperature is measured accurately, the rock thermal diffusivity must be set within an error margin of less than 3 %, but it is nearly impossible under real conditions.Increasing the number of temperature measurements diminishes the sensitivity to measurement errors, with the optimal efficacy achieved at 10 measurements, rendering further increments impractical.Therefore, the algorithm’s stability and the solution’s sensitivity of the inverse problem of determining the reservoir thermal diffusivity for a given operating period of the well relative to temperature measurement errors were found. The results show that a 1 % error in temperature measurements leads to a standard deviation of about 6 % from the true value.https://uzakufismat.elpub.ru/jour/article/view/72oil reservoirtemperature loggingmeasurement errorgeological uncertaintyinverse problemnumerical modeling
spellingShingle K. A. Potashev
D. R. Salimyanova
A. B. Mazo
A. A. Davletshin
A. V. Kosterin
Sensitivity to Initial Data Errors in Interpreting Temperature Logging of an Isolated Injection Well Segment
Учёные записки Казанского университета: Серия Физико-математические науки
oil reservoir
temperature logging
measurement error
geological uncertainty
inverse problem
numerical modeling
title Sensitivity to Initial Data Errors in Interpreting Temperature Logging of an Isolated Injection Well Segment
title_full Sensitivity to Initial Data Errors in Interpreting Temperature Logging of an Isolated Injection Well Segment
title_fullStr Sensitivity to Initial Data Errors in Interpreting Temperature Logging of an Isolated Injection Well Segment
title_full_unstemmed Sensitivity to Initial Data Errors in Interpreting Temperature Logging of an Isolated Injection Well Segment
title_short Sensitivity to Initial Data Errors in Interpreting Temperature Logging of an Isolated Injection Well Segment
title_sort sensitivity to initial data errors in interpreting temperature logging of an isolated injection well segment
topic oil reservoir
temperature logging
measurement error
geological uncertainty
inverse problem
numerical modeling
url https://uzakufismat.elpub.ru/jour/article/view/72
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AT aadavletshin sensitivitytoinitialdataerrorsininterpretingtemperatureloggingofanisolatedinjectionwellsegment
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