Open AccessStudy on Processing Method of Acoustic Emission Signal for Hydraulic Fracture Measurement
Author(s) -
Haifeng Fu,
Xinquan Zheng,
Bo Chen,
Tiancheng Liang,
Jinping Qiu,
Feng Chen,
Yunzhi Liu,
Jiaojun Rong
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1894/1/012098
Subject(s) - acoustic emission , fracture (geology) , hydraulic fracturing , signal (programming language) , acoustics , geology , materials science , computer science , geotechnical engineering , physics , programming language
Hydraulic fracturing has become a key technology for the unconventional oil and gas development. Due to the complexity of geological conditions and the limitation of monitoring technology, it is still very difficult to accurately understand the three-dimensional distribution characteristics of hydraulic fractures. Based on the acoustic emission monitoring and three-dimensional laser scanning for large scale (762 mm * 762 mm * 914 mm) hydraulic fracturing test, hydraulic fracture morphology characterization is measured. The control method of acoustic emission signal quality based on amplitude, root-mean-square phase and multi-channel contrast signal recognition was explored. A multi-parameter constrained grid search and location method was established, which significantly improved the location accuracy and realized the dynamic and static real-time characterization of hydraulic fracture space expansion under indoor conditions. The results show that: based on laser scanning technology, the detailed characterization method of hydraulic fracture morphology is established, and the fracture morphology in laboratory experiment can be improved from two-dimensional observation to three-dimensional display. Due to mutual influence of natural fracture and in situ stress field, the hydraulic fracture appears complex geometry such as turning and bifurcation. The accuracy of acoustic emission location is improved by 10%, and the consistency with the actual fracture scale reaches 95%. The processing method of acoustic emission signal in this paper can be directly used in the optimization of field microseismic monitoring to guide the evaluation of unconventional reservoir stimulation, which shows a broad application prospect.