## Abstract

Hydraulic fracturing is applied ubiquitously in unconventional hydrocarbon reservoir development to increase the well productivity. To design a frac job, an injection falloff diagnostic test, such as minifrac test, is conducted first to determine key formation properties and frac operational parameters, including fracture closure pressure. In low permeability formations, the conventional pressure falloff analysis (i.e. G-function) is not practical to identify the fracture closure since it requires several days of well shut-in to collect enough pressure falloff data to reveal the fracture closure. In SPE-187495-PA, the authors show that it is possible to develop an empirical equation to predict the fracture closure pressure (Pc) from instantaneous shut-in pressure (ISIP), the first falloff data point, by regressive analysis on datasets from minifrac tests for conventional formations, including G-function estimated Pc, ISIP, petrophysical and mechanical properties. Since petrophysical and mechanical properties could be estimated from cores and wireline logs, the application of this equation requires a minifrac test to have a very short falloff period only to estimate ISIP. The objective of this work is to extend that equation for unconventional formations by introducing appropriate deviation terms for tight-sand and shale formations, respectively, in order to reduce the discrepancy between predicted Pc and G-function estimated Pc.

To this end, several datasets, each of which contain the same attributes, are collected from publications for shale and tight-sand formations. Part of datasets are selected for developing respective deviation terms, for shale and tight-sand, to be added to the empirical equation, while the remaining datasets are used to test the respective new equation. Then a regression analysis is performed between Pc differences and the individual petrophysical and mechanical properties for shale and tight-sand datasets separately. Eventually, two deviation terms have been derived and incorporated to the empirical equation, one for shale and another one for tight formations.

The deviation term for tight-sand formations correlate strongly with the rock mechanical properties, while the other with the rock mechanical properties and the formation porosity. Several field cases have been used to validate the empirical equation with respective deviation terms and the results show that the new formulae predict the fracture closure pressure with a relative absolute error less than 5% compared to those estimated from the G-function analysis for both the shale and the tight formations cases which are not used in developing respective deviation terms.

To this end, several datasets, each of which contain the same attributes, are collected from publications for shale and tight-sand formations. Part of datasets are selected for developing respective deviation terms, for shale and tight-sand, to be added to the empirical equation, while the remaining datasets are used to test the respective new equation. Then a regression analysis is performed between Pc differences and the individual petrophysical and mechanical properties for shale and tight-sand datasets separately. Eventually, two deviation terms have been derived and incorporated to the empirical equation, one for shale and another one for tight formations.

The deviation term for tight-sand formations correlate strongly with the rock mechanical properties, while the other with the rock mechanical properties and the formation porosity. Several field cases have been used to validate the empirical equation with respective deviation terms and the results show that the new formulae predict the fracture closure pressure with a relative absolute error less than 5% compared to those estimated from the G-function analysis for both the shale and the tight formations cases which are not used in developing respective deviation terms.

Original language | English |
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Title of host publication | SPE Liquids-Rich Basins Conference - North America, 7-8 November, Odessa, Texas, USA |

Publisher | Society of Petroleum Engineers |

ISBN (Print) | 9781613997031 |

DOIs | |

Publication status | Published - 2019 |