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Title: Predictions of macro-scale fracture geometries from acoustic emission point cloud data in a hydraulic fracturing experiment

Abstract

Observations of laboratory fracture testing by means of acoustic emission (AE) can provide a wealth of information regarding the fracturing process and the subsequent damage of the material or structure under load. A method for determining the structure of macro-scale fractures from a point cloud of AE events was developed and tested at the laboratory scale. An unconfined hydraulic fracturing experiment was performed on granite while monitoring acoustic emissions from six piezoelectric transducers on the surfaces of the specimen. The granite specimen dimensions were 30 × 30 × 25 cm 3. The motivation of the AE analysis was to provide location information for a secondary wellbore placement which intersects the hydraulic fracture to complete a hydraulically connected binary well-hydraulic fracture system. Information gained from the 3D event source locations was used to optimize the location and orientation of secondary production well placement to intersect the induced hydraulic fracture. A direct method was developed to predict the location, orientation and shape of the hydraulic fracture from a dense cloud of AE events. The predicted fracture plane, which was assumed to be planar, was rotated in both the pitch and roll directions, while an average error of AE event distance between themore » assumed plane and the individual event locations was determined for each rotation iteration, resulting with a predicted fracture plane in the minimum error orientation. Post-test fracture observations were made and digitized in 3D space from coring and slabbing the granite specimen. The actual fracture observations were compared with the predicted fracture structure from AE and showed marked correlation. In conclusion, the simple method of determining macro-scale fracture location, orientation, and extents provided a useful tool for materials that exhibit large and disperse clouds of AE activity where coalesced fracture structure is not apparent.« less

Authors:
 [1]; ORCiD logo [1];  [1]
  1. Colorado School of Mines, Golden, CO (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1480051
Report Number(s):
LA-UR-18-28364
Journal ID: ISSN 2190-0558
Grant/Contract Number:  
AC52-06NA25396
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Petroleum Exploration and Production Technology
Additional Journal Information:
Journal Name: Journal of Petroleum Exploration and Production Technology; Journal ID: ISSN 2190-0558
Publisher:
Springer Nature - Springer Berlin Heidelberg
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; Earth Sciences

Citation Formats

Hampton, Jesse, Gutierrez, Marte, and Frash, Luke. Predictions of macro-scale fracture geometries from acoustic emission point cloud data in a hydraulic fracturing experiment. United States: N. p., 2018. Web. doi:10.1007/s13202-018-0547-z.
Hampton, Jesse, Gutierrez, Marte, & Frash, Luke. Predictions of macro-scale fracture geometries from acoustic emission point cloud data in a hydraulic fracturing experiment. United States. doi:10.1007/s13202-018-0547-z.
Hampton, Jesse, Gutierrez, Marte, and Frash, Luke. Fri . "Predictions of macro-scale fracture geometries from acoustic emission point cloud data in a hydraulic fracturing experiment". United States. doi:10.1007/s13202-018-0547-z. https://www.osti.gov/servlets/purl/1480051.
@article{osti_1480051,
title = {Predictions of macro-scale fracture geometries from acoustic emission point cloud data in a hydraulic fracturing experiment},
author = {Hampton, Jesse and Gutierrez, Marte and Frash, Luke},
abstractNote = {Observations of laboratory fracture testing by means of acoustic emission (AE) can provide a wealth of information regarding the fracturing process and the subsequent damage of the material or structure under load. A method for determining the structure of macro-scale fractures from a point cloud of AE events was developed and tested at the laboratory scale. An unconfined hydraulic fracturing experiment was performed on granite while monitoring acoustic emissions from six piezoelectric transducers on the surfaces of the specimen. The granite specimen dimensions were 30 × 30 × 25 cm3. The motivation of the AE analysis was to provide location information for a secondary wellbore placement which intersects the hydraulic fracture to complete a hydraulically connected binary well-hydraulic fracture system. Information gained from the 3D event source locations was used to optimize the location and orientation of secondary production well placement to intersect the induced hydraulic fracture. A direct method was developed to predict the location, orientation and shape of the hydraulic fracture from a dense cloud of AE events. The predicted fracture plane, which was assumed to be planar, was rotated in both the pitch and roll directions, while an average error of AE event distance between the assumed plane and the individual event locations was determined for each rotation iteration, resulting with a predicted fracture plane in the minimum error orientation. Post-test fracture observations were made and digitized in 3D space from coring and slabbing the granite specimen. The actual fracture observations were compared with the predicted fracture structure from AE and showed marked correlation. In conclusion, the simple method of determining macro-scale fracture location, orientation, and extents provided a useful tool for materials that exhibit large and disperse clouds of AE activity where coalesced fracture structure is not apparent.},
doi = {10.1007/s13202-018-0547-z},
journal = {Journal of Petroleum Exploration and Production Technology},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {9}
}

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