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Title: Distributed Acoustic Sensing (DAS) Data for Periodic Hydraulic Tests

Abstract

California State University Long Beach evaluated hydraulic connectivity among geothermal wells using Periodic Hydraulic Testing (PHT) and Distributed Acoustic Sensing (DAS). The principal was to create a pressure signal in one well and observe the responding pressure signals in one or more observation wells to assess the permeability and storage of the fracture network that connects the two wells. DAS measured strain at mHz frequency in monitoring wells in response to PHT.

Authors:
;
Publication Date:
Research Org.:
DOE Geothermal Data Repository; California State University Long Beach
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Program (EE-2C)
OSTI Identifier:
1432544
Report Number(s):
929
DOE Contract Number:
EE0006763
Resource Type:
Data
Data Type:
Numeric Data
Country of Publication:
United States
Availability:
GDRHelp@ee.doe.gov
Language:
English
Subject:
15 Geothermal Energy; geothermal; energy; DAS; distributed acoustic sensing; Mirror Lake; New Hampshire; geomechanics; periodic hydraulic tests; Matlab; acoustic sensing data

Citation Formats

Coleman, Thomas, and Becker, Matthew. Distributed Acoustic Sensing (DAS) Data for Periodic Hydraulic Tests. United States: N. p., 2017. Web. doi:10.15121/1432544.
Coleman, Thomas, & Becker, Matthew. Distributed Acoustic Sensing (DAS) Data for Periodic Hydraulic Tests. United States. doi:10.15121/1432544.
Coleman, Thomas, and Becker, Matthew. Thu . "Distributed Acoustic Sensing (DAS) Data for Periodic Hydraulic Tests". United States. doi:10.15121/1432544. https://www.osti.gov/servlets/purl/1432544.
@article{osti_1432544,
title = {Distributed Acoustic Sensing (DAS) Data for Periodic Hydraulic Tests},
author = {Coleman, Thomas and Becker, Matthew},
abstractNote = {California State University Long Beach evaluated hydraulic connectivity among geothermal wells using Periodic Hydraulic Testing (PHT) and Distributed Acoustic Sensing (DAS). The principal was to create a pressure signal in one well and observe the responding pressure signals in one or more observation wells to assess the permeability and storage of the fracture network that connects the two wells. DAS measured strain at mHz frequency in monitoring wells in response to PHT.},
doi = {10.15121/1432544},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jul 06 00:00:00 EDT 2017},
month = {Thu Jul 06 00:00:00 EDT 2017}
}

Dataset:

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  • Hydraulic responses from periodic hydraulic tests conducted at the Mirror Lake Fractured Rock Research Site, during the summer of 2015. These hydraulic responses were measured also using distributed acoustic sensing (DAS) which is cataloged in a different submission under this grant number. The tests are explained in detail in Matthew Cole's MS Thesis which is cataloged here. The injection and drawdown data and the codes used to analyze the data. Sinusoidal Data is a Matlab data file containing a data table for each period-length test. Within each table is a column labeled: time (seconds since beginning of pumping), Inj_m3pm (formationmore » injection in cubic meters per minute), and head for each observation well (meters). The three Matlab script files (*.m) were used to analyze hydraulic responses from the data file above. High-Pass Sinusoid is a routine for filtering the data, computing the FFT, and extracting phase and amplitude values. Borestore is a routine which contains the borehole storage analytic solution and compares modeled amplitude and phase from this solution to computed amplitude and phase from the data. Patsearch Borestore is a routine containing the built-in pattern search optimization method. This minimizes the total error between modeled and actual amplitude and phase in Borestore. Comments within the script files contain more specific instructions for their use.« less
  • These data were collected in the laboratory located at California State University Long Beach. They consist of DAS data collected from a fiber optic cable placed in a tank of water, subjected to oscillating head. These tests are described in the article linked below.
  • The extraction of heat from hot rock requires circulation of fluid through fracture networks. Because the geometry and connectivity of these fractures determines the efficiency of fluid circulation, many tools are used to characterize fractures before and after development of the reservoir. Under this project, a new tool was developed that allows hydraulic connectivity between geothermal boreholes to be identified. Nanostrain in rock fractures is measured using fiber optic distributed acoustic sensing (DAS). This strain is measured in one borehole in response to periodic pressure pulses induced in another borehole. The strain in the fractures represents hydraulic connectivity between wells.more » DAS is typically used at frequencies of Hz to kHz, but strain at mHz frequencies were measured for this project. The tool was demonstrated in the laboratory and in the field. In the laboratory, strain in fiber optic cables was measured in response to compression due to oscillating fluid pressure. DAS recorded strains as small as 10 picometer/m in response to 1 cm of water level change. At a fractured crystalline rock field site, strain was measured in boreholes. Fiber-optic cable was mechanically coupled borehole walls using pressured flexible liners. In one borehole 30 m from the oscillating pumping source, pressure and strain were measured simultaneously. The DAS system measured fracture displacement at frequencies of less than 1 mHz (18 min periods) and amplitudes of less than 1 nm, in response to fluid pressure changes of less 20 Pa (2 mm of water). The attenuation and phase shift of the monitored strain signal is indicative of the permeability and storage (compliance) of the fracture network that connects the two wells. The strain response as a function of oscillation frequency is characteristic of the hydraulic structure of the formation. This is the first application of DAS to the measurement of low frequency strain in boreholes. It has enormous potential for monitoring geothermal reservoirs for purposes of understanding reservoir compliance and for assuring security of injection fluids. Periodic pressure pulses can be induced by oscillating injection or pumping during operation so the system could provide real time reservoir data. DAS cable may already be installed at a site as it is becoming increasingly used for seismic observation. Simulations conducted for this project indicate that strain should be propagated through borehole cements, so observations can be made outside of well casing. In uncased holes, the cable would need to be mechanically coupled to the borehole wall to provide measurements. One option would be to install fiber into cemented and abandoned boreholes to extend their utility.« less
  • In September 2013, an experiment using Distributed Acoustic Sensing (DAS) was conducted at Garner Valley, a test site of the University of California Santa Barbara (Lancelle et al., 2014). This submission includes all DAS data recorded during the experiment. The sampling rate for all files is 1000 samples per second. Any files with the same filename but ending in _01, _02, etc. represent sequential files from the same test. Locations of the sources are plotted on the basemap in GDR submission 481, titled: "PoroTomo Subtask 3.2 Sample data from a Distributed Acoustic Sensing experiment at Garner Valley, California (PoroTomo Subtaskmore » 3.2)." Lancelle, C., N. Lord, H. Wang, D. Fratta, R. Nigbor, A. Chalari, R. Karaulanov, J. Baldwin, and E. Castongia (2014), Directivity and Sensitivity of Fiber-Optic Cable Measuring Ground Motion using a Distributed Acoustic Sensing Array (abstract # NS31C-3935), AGU Fall Meeting. 
https://agu.confex.com/agu/fm1/meetingapp.cgi#Paper/19828 The e-poster is available at: https://agu.confex.com/data/handout/agu/fm14/Paper_19828_handout_696_0.pdf« less
  • In September 2013, an experiment using Distributed Acoustic Sensing (DAS) was conducted at Garner Valley, a test site of the University of California Santa Barbara (Lancelle et al., 2014). This submission includes noise cross-correlation functions (NCF) . Each file includes a NCF between two channels. The name of each channel denotes the distance in meters from starting point of the fiber-optic cable. Lancelle, C., N. Lord, H. Wang, D. Fratta, R. Nigbor, A. Chalari, R. Karaulanov, J. Baldwin, and E. Castongia (2014), Directivity and Sensitivity of Fiber-Optic Cable Measuring Ground Motion using a Distributed Acoustic Sensing Array (abstract # NS31C-3935),more » AGU Fall Meeting. https://agu.confex.com/agu/fm14/meetingapp.cgi#Paper/19828 The e-poster is available at: https://agu.confex.com/data/handout/agu/fm14/Paper_19828_handout_696_0.pdf« less