Page 206 - Reservoir Geomechanics

188 Reservoir geomechanics

stress-induced deformation at mid-crustal depths and sample relatively large volumes
of rock, and focal plane mechanisms provide data on both the orientation and relative
magnitude of the in situ stress field. The principal disadvantage of utilizing earthquake
focal plane mechanisms as stress indicators is that focal plane mechanisms record defor-
mation and not stress. Thus, the P- and T-axes are, by definition, the bisectors of the
dilatational and compressional quadrants, respectively, and are not the maximum and
minimum principal stress directions (as is often assummed) but are the compressional
and extensional strain directions for the two possible faults. Most crustal earthquakes
appear to occur on pre-existing faults (rather than resulting from new fault breaks),
the slip vector is a function both of the orientation of the fault and the orientation
and relative magnitude of the principal stresses. The P- and T-axes of the focal plane
mechanism do not correlate directly with principal stress directions. Because the coef-
ficient of friction of many rocks is often in the range of 0.6–0.8 (Byerlee 1978), it has
been suggested that the expected angle between the fault plane and the direction of
maximum principal stress should be plotted 30 from the fault plane (Raleigh, Healy
◦
et al. 1972). However, this requires knowledge of the actual fault plane, which is fre-
quently not the case. If the auxiliary plane of the focal mechanism was mistakenly
selected as the fault plane (Chapter 5), the presumed stress orientation would be off
◦
by ∼45 .
To optimize the use of focal plane mechanism data for determining stress orientations
it is necessary to consider multiple events in a given region and use either the average
P-axis direction as the maximum horizontal stress direction or to formally invert a
group of focal plane mechanisms to determine the orientation and relative magnitude
of the principal stress tensor (see, for example, Angelier 1979; Gephart and Forsyth
1984; Michael 1987).
The assignment of A, B, C and D qualities to wellbore breakout data is based on
the frequency, overall length and consistency of occurrence of breakouts in a given
well. The standard deviations associated with the respective qualities shown in Table
6.1 were determined from our empirical experience working with breakout data in a
number of boreholes. High standard deviations (>∼25 ) represent either very scattered,
◦
or bi-modal, distributions due to a variety of factors – if the rock is strong compared
to the stress concentration, breakouts will be poorly developed. On the other hand,
the rock might be very weak and failure so pervasive that it is difficult to distinguish
between stress-induced breakouts and more pervasive washouts. This is why utilizing
the criterion for distinguishing breakouts from key seats and washouts (as discussed
later in this chapter) is so important.
To calculate the mean breakout direction, θ m , and the standard deviation, sd, of a
set of breakouts on a given side of a well, we utilize Fisher statistics and let θ i (i =
◦
1, . . ., N) denote the observed breakout directions in the range 0–360 . First, we define

(6.10)
1 i = cos θ i and m i = sin θ i