Active Source Monitoring of Cross-Well Seismic Travel Time for Stress-Induced Changes.pdf
|
|
Active Source Monitoring of Cross-Well Seismic Travel Time for Stress-Induced Changes
Page 1
281
Bulletin of the Seismological Society of America, Vol. 97, No. 1B, pp. 281–293, February 2007, doi: 10.1785/0120060120
Active Source Monitoring of Cross-Well Seismic Travel Time
for Stress-Induced Changes
by Paul G. Silver, Thomas M. Daley, Fenglin Niu, and Ernest L. Majer
Abstract
We have conducted a series of cross-well experiments to continuously
measure in situ temporal variations in seismic velocity at two test sites: building 64
(B64) and Richmond Field Station (
RFS
) of the Lawrence Berkeley National
Laboratory in California. A piezoelectric source was used to generate highly repeat-
able signals, and a string of 24 hydrophones was used to record the signals. The B64
experiment was conducted utilizing two boreholes 17 m deep and 3 m apart for
160 h. At
RFS
, we collected a 36-day continuous record in a cross-borehole facility
using two 70-m-deep holes separated by 30 m. With signal enhancement techniques
we were able to achieve a precision of 6.0 nsec and 10 nsec in delay-time esti-
mation from stacking of 1-hr records during the 7- and 35-day observation pe-
riods at the B64 and
RFS
sites, which correspond to 3 and 0.5 ppm of their travel
times, respectively. Delay time measured at B64 has a variation of 2 lsec in the
160-hr period and shows a strong and positive correlation with the barometric pres-
sure change at the site. At
RFS
, after removal of a linear trend, we find a delay-time
variation of 2.5 lsec, which exhibits a significant negative correlation with baro-
metric pressure. We attribute the observed correlations to stress sensitivity of seismic
velocity known from laboratory studies. The positive and negative sign observed in
the correlation is likely related to the expected near- and far-field effects of this stress
dependence in a poroelastic medium. The stress sensitivity is estimated to be 10
6
/
Pa and 10
7
/Pa at the B64 and
RFS
site, respectively.
Introduction
Measuring and monitoring changes in the subsurface
stress field has been a long-sought goal of the geophysical
community over recent decades. The monitoring of time-
varying stress is a crucial diagnostic for at least two impor-
tant fields of study: the nucleation and triggering of earth-
quakes and the distribution of reservoir fluids under the
influence of withdrawal or injection. Knowledge of the sub-
surface stress field is currently inferred from surface mea-
surements or single-point subsurface measurements. For
example, geodesy provides important constraints on the sur-
face deformation field, which can be related to seismogenic
stress through an assumed structural model of the rheology,
whereas borehole strainmeters can give point measurements
of temporal variation in strain. Thus, the constraints on 3D
spatial distribution of stress and strain from current mea-
surements are limited. The surface constraints need to be
combined with other techniques that, while not as directly
related to stress and strain, have superior depth resolution.
281
Bulletin of the Seismological Society of America, Vol. 97, No. 1B, pp. 281–293, February 2007, doi: 10.1785/0120060120
Active Source Monitoring of Cross-Well Seismic Travel Time
for Stress-Induced Changes
by Paul G. Silver, Thomas M. Daley, Fenglin Niu, and Ernest L. Majer
Abstract
We have conducted a series of cross-well experiments to continuously
measure in situ temporal variations in seismic velocity at two test sites: building 64
(B64) and Richmond Field Station (
RFS
) of the Lawrence Berkeley National
Laboratory in California. A piezoelectric source was used to generate highly repeat-
able signals, and a string of 24 hydrophones was used to record the signals. The B64
experiment was conducted utilizing two boreholes 17 m deep and 3 m apart for
160 h. At
RFS
, we collected a 36-day continuous record in a cross-borehole facility
using two 70-m-deep holes separated by 30 m. With signal enhancement techniques
we were able to achieve a precision of 6.0 nsec and 10 nsec in delay-time esti-
mation from stacking of 1-hr records during the 7- and 35-day observation pe-
riods at the B64 and
RFS
sites, which correspond to 3 and 0.5 ppm of their travel
times, respectively. Delay time measured at B64 has a variation of 2 lsec in the
160-hr period and shows a strong and positive correlation with the barometric pres-
sure change at the site. At
RFS
, after removal of a linear trend, we find a delay-time
variation of 2.5 lsec, which exhibits a significant negative correlation with baro-
metric pressure. We attribute the observed correlations to stress sensitivity of seismic
velocity known from laboratory studies. The positive and negative sign observed in
the correlation is likely related to the expected near- and far-field effects of this stress
dependence in a poroelastic medium. The stress sensitivity is estimated to be 10
6
/
Pa and 10
7
/Pa at the B64 and
RFS
site, respectively.
Introduction
Measuring and monitoring changes in the subsurface
stress field has been a long-sought goal of the geophysical
community over recent decades. The monitoring of time-
varying stress is a crucial diagnostic for at least two impor-
tant fields of study: the nucleation and triggering of earth-
quakes and the distribution of reservoir fluids under the
influence of withdrawal or injection. Knowledge of the sub-
surface stress field is currently inferred from surface mea-
surements or single-point subsurface measurements. For
example, geodesy provides important constraints on the sur-
face deformation field, which can be related to seismogenic
stress through an assumed structural model of the rheology,
whereas borehole strainmeters can give point measurements
of temporal variation in strain. Thus, the constraints on 3D
spatial distribution of stress and strain from current mea-
surements are limited. The surface constraints need to be
combined with other techniques that, while not as directly
related to stress and strain, have superior depth resolution.
