Applying Statistical Methods to Assess Fractured Reservoirs Relying on Field Data

The presence of fractures in reservoirs can have both a negative and a positive impact on the technical and economic indicators of field development and thus an early classification of fractures is an important requisite. Identifying the type of a fractured reservoir at the initial stages of develop...

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Главные авторы:	Shchekin, A. I., Щекин, А. И.
Формат:	Статья
Язык:	Russian
Опубликовано:	Georesursy LLC 2025
Темы:	Bootstrapping Lorenz curve Classification of fractured reservoirs Fracture impact coefficient Fractured reservoirs
Online-ссылка:	https://dspace.ncfu.ru/handle/123456789/30460
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id	ir-123456789-30460
record_format	dspace
spelling	ir-123456789-304602025-05-15T11:36:41Z Applying Statistical Methods to Assess Fractured Reservoirs Relying on Field Data Shchekin, A. I. Щекин, А. И. Bootstrapping Lorenz curve Classification of fractured reservoirs Fracture impact coefficient Fractured reservoirs The presence of fractures in reservoirs can have both a negative and a positive impact on the technical and economic indicators of field development and thus an early classification of fractures is an important requisite. Identifying the type of a fractured reservoir at the initial stages of development is a clue to selecting an optimal type of model and field development system. The paper evaluates the applicability of the cumulative production indicator and the productivity index of wells to determine the type of fractured reservoir with the help of a statistical method for analyzing the Lorenz curve and the Gini coefficient (as applied to determine the impact of fractures) with small data samples and at the initial stages of development. A method of mathematical statistics namely the bootstrap method is used in this paper in order to study the fracture impact coefficient for a small number of wells. This method is based on the repeated generation of random samples multitude from the original data set and their subsequent statistical analysis. Modeling of samples was carried out by means of a random number generator available in spreadsheets. The results of a research proved that the use of indicators such as cumulative production and productivity index to identify fractured reservoirs with a small number of wells produced the comparable results. To increase the reliability of classification for a small number of wells, a data sample is required that will most fully describe the field. It is possible to obtain a representative sample of data for an objective analysis of the distribution and influence of fracture systems by placing wells covering the entire area of the field. In the early stages of development, due to the low production volumes and short periods of well operation, it is recommended to use the productivity index for the analysis. 2025-05-15T11:35:48Z 2025-05-15T11:35:48Z 2025 Статья Shchekin A.I. Applying Statistical Methods to Assess Fractured Reservoirs Relying on Field Data // Georesursy. - 2025. - 27 (1). - pp. 275 - 283. - DOI: 10.18599/grs.2025.1.3 https://dspace.ncfu.ru/handle/123456789/30460 ru Georesursy application/pdf application/pdf Georesursy LLC
institution	СКФУ
collection	Репозиторий
language	Russian
topic	Bootstrapping Lorenz curve Classification of fractured reservoirs Fracture impact coefficient Fractured reservoirs
spellingShingle	Bootstrapping Lorenz curve Classification of fractured reservoirs Fracture impact coefficient Fractured reservoirs Shchekin, A. I. Щекин, А. И. Applying Statistical Methods to Assess Fractured Reservoirs Relying on Field Data
description	The presence of fractures in reservoirs can have both a negative and a positive impact on the technical and economic indicators of field development and thus an early classification of fractures is an important requisite. Identifying the type of a fractured reservoir at the initial stages of development is a clue to selecting an optimal type of model and field development system. The paper evaluates the applicability of the cumulative production indicator and the productivity index of wells to determine the type of fractured reservoir with the help of a statistical method for analyzing the Lorenz curve and the Gini coefficient (as applied to determine the impact of fractures) with small data samples and at the initial stages of development. A method of mathematical statistics namely the bootstrap method is used in this paper in order to study the fracture impact coefficient for a small number of wells. This method is based on the repeated generation of random samples multitude from the original data set and their subsequent statistical analysis. Modeling of samples was carried out by means of a random number generator available in spreadsheets. The results of a research proved that the use of indicators such as cumulative production and productivity index to identify fractured reservoirs with a small number of wells produced the comparable results. To increase the reliability of classification for a small number of wells, a data sample is required that will most fully describe the field. It is possible to obtain a representative sample of data for an objective analysis of the distribution and influence of fracture systems by placing wells covering the entire area of the field. In the early stages of development, due to the low production volumes and short periods of well operation, it is recommended to use the productivity index for the analysis.
format	Статья
author	Shchekin, A. I. Щекин, А. И.
author_facet	Shchekin, A. I. Щекин, А. И.
author_sort	Shchekin, A. I.
title	Applying Statistical Methods to Assess Fractured Reservoirs Relying on Field Data
title_short	Applying Statistical Methods to Assess Fractured Reservoirs Relying on Field Data
title_full	Applying Statistical Methods to Assess Fractured Reservoirs Relying on Field Data
title_fullStr	Applying Statistical Methods to Assess Fractured Reservoirs Relying on Field Data
title_full_unstemmed	Applying Statistical Methods to Assess Fractured Reservoirs Relying on Field Data
title_sort	applying statistical methods to assess fractured reservoirs relying on field data
publisher	Georesursy LLC
publishDate	2025
url	https://dspace.ncfu.ru/handle/123456789/30460
work_keys_str_mv	AT shchekinai applyingstatisticalmethodstoassessfracturedreservoirsrelyingonfielddata AT ŝekinai applyingstatisticalmethodstoassessfracturedreservoirsrelyingonfielddata
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Applying Statistical Methods to Assess Fractured Reservoirs Relying on Field Data

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