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Title: Natural and Hydraulic Fracture Density Prediction and Identification of Controllers

Abstract

Discrete Fracture Networks (DFN’s) incorporated into hydraulic fracture modeling and reservoir simulation are typically constructed and calibrated to all available high-quality natural fracture data from image logs and core, which generally results in an extremely limited calibration data set. To extrapolate these data over large areas, more broadly sampled data sets, such as discontinuity-related 3-D seismic attributes are often used. Broad spatial trending methodologies can potentially misrepresent natural fracture systems through over-reliance on seismic attributes that are commonly influenced by noise. The Hydraulic Fracture Test Site (HFTS) provides a rare insight of the subsurface natural fracture network and controlling factors on fracture distribution from a mechanical and lithological standpoint. The physical occurrence of hydraulic fractures and their interaction and relationship to preexisting natural fractures can be predicted using analytical models. Such model outputs can be applied to provide higher confidence when developing DFN’s.

Authors:
 [1];  [1];  [1]
  1. Laredo Petroleum
Publication Date:
Research Org.:
Gas Technology Institute
Sponsoring Org.:
USDOE Office of Fossil Energy (FE)
OSTI Identifier:
1477764
Report Number(s):
NoneURTeC:2934611
DOE Contract Number:  
FE0024292
Resource Type:
Conference
Resource Relation:
Conference: Unconventional Resources Technology Conference held in Houston, Texas, USA, 23-25 July 2018
Country of Publication:
United States
Language:
English

Citation Formats

Campbell, Whitney, Wicker, Joe, and Courtier, James. Natural and Hydraulic Fracture Density Prediction and Identification of Controllers. United States: N. p., 2018. Web. doi:10.15530/urtec-2018-2934611.
Campbell, Whitney, Wicker, Joe, & Courtier, James. Natural and Hydraulic Fracture Density Prediction and Identification of Controllers. United States. doi:10.15530/urtec-2018-2934611.
Campbell, Whitney, Wicker, Joe, and Courtier, James. Tue . "Natural and Hydraulic Fracture Density Prediction and Identification of Controllers". United States. doi:10.15530/urtec-2018-2934611. https://www.osti.gov/servlets/purl/1477764.
@article{osti_1477764,
title = {Natural and Hydraulic Fracture Density Prediction and Identification of Controllers},
author = {Campbell, Whitney and Wicker, Joe and Courtier, James},
abstractNote = {Discrete Fracture Networks (DFN’s) incorporated into hydraulic fracture modeling and reservoir simulation are typically constructed and calibrated to all available high-quality natural fracture data from image logs and core, which generally results in an extremely limited calibration data set. To extrapolate these data over large areas, more broadly sampled data sets, such as discontinuity-related 3-D seismic attributes are often used. Broad spatial trending methodologies can potentially misrepresent natural fracture systems through over-reliance on seismic attributes that are commonly influenced by noise. The Hydraulic Fracture Test Site (HFTS) provides a rare insight of the subsurface natural fracture network and controlling factors on fracture distribution from a mechanical and lithological standpoint. The physical occurrence of hydraulic fractures and their interaction and relationship to preexisting natural fractures can be predicted using analytical models. Such model outputs can be applied to provide higher confidence when developing DFN’s.},
doi = {10.15530/urtec-2018-2934611},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {7}
}

Conference:
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