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The AAPG/Datapages Combined Publications Database
GCAGS Transactions
Abstract
EXTENDED ABSTRACT: Calibration of Predicted Pore Pressure: Perceptions
and Pitfalls
Selim Shaker
11221 Gladewick Dr., Houston, Texas 77077
EXTENDED ABSTRACT
Transforming petrophysical properties into pore pressure (PP) is a very challenging process to which unscientific calibration templates are often applied.
The assumption that measured pore pressure in permeable beds (sand) is equal to predicted pore pressure in low permeable beds (shale, mud) does not hold true in most cases. If it were true, drilling problems and hydrocarbon trapping risk would be negligible.
Before drilling, seismic interval velocity
extracted from root mean square
(RMS)
velocity
is widely used for this transformation purpose.
Velocity
picks from
normal
move out (NMO)
gathers
should be checked against semblance for quality control.
Sequence
stratigraphy can help in picking the shale
velocity
intervals. During drilling,
a
bundle of data becomes available for PP prediction (PPP), measurements, and
calibration.
Logging while drilling (LWD), measurement while drilling (MWD), conventional
logs, mud log, and direct PP measurements in the sand (RFT [Repeat Formation
Tester],
MDT [Modular Formation Dynamics Tester], DFT [Drilling Formation Tester], FPWD
[Formation Pressure While Drilling), and engineering drilling records are used
to establish
the subsurface geopressure profile to reach the target objective in a safe
and economically
feasible manner.
Seismic velocity
of a proposed wildcat location and data derived from offset
wells,
such as sonic and resistivity, are utilized to predict the subsurface geopressure
profile. A
pre-drilling geopressure model is built based on the variables of
velocity
picks, normal
compaction trends slope, and effective stress exponents.
The prediction of pore pressure is primarily established based on the divergence
of
the petrophysical measurements from the normal compaction trend. In the transition
zone between the hydrostatically pressured and geopressured systems, formation
water
is expelled gradually from sediments due to pressure gradient drop from deeper
to shallower
depth. In this transition zone velocity
, resistivity, and density increase
downward
concurrent with the rate of the dewatering process. The Normal Compaction Trend
(NCT) represents the optimum fitted linear trend of these measured data in
the low permeable
beds in this transition zone. Inversely, in the geopressured system (where
water
is no longer capable of escaping)
velocity
, density, and resistivity measurements
decrease
in the low permeable beds.
The effective stress model of transforming the petrophysical measurement (e.g., sonic slowness) to pore pressure in the fine clastic (shale, mud, fine silt) beds is based on:
PP = PS – ES
PPz = OBz– (OBz– Pnz) * (ΔTn/ΔTo)^X
where PP = predicted pore pressure, PS = principal stress = overburden (OB) in case of passive structure areas, ES = effective stress, Z = depth to point of measurement, Pn = the normal pressure at depth Z, ΔTn = the assumed normal sonic slowness at depth Z (calculated from the NCT), ΔTo = the observed (measured) sonic slowness at depth Z, and X = PP transformation exponent (variable with age/basin location).
Therefore, the keystone for this prediction practice is the value of ΔTn /ΔTo, which is mainly conveyed as a result of establishing the slope on the NCT (Fig. 1).
During and post-drilling, a calibration fitting process should be applied to the modeled values of shale beds. However, some of these calibrating methods are based on illogical assumptions, such as:
- Predicting pore pressure in sand
using
the same effective stress model designed for shale (Fig. 2).
- Assuming measured pore pressure in sand is equal to predicted pore pressure in shale (Fig. 2).
- Applying universal effective stress exponent.
- Breaking of the normal compaction trend to selective segments, due to faulting or other reasons, to fit the predicted pore pressure with the drilling records and the measured pressure data during and post drilling is another interpretation pitfall. This leads to incorrect adjustments of the .Tn/.To values for the purpose of calibration and consequently compromises the effective stress transformation model (Fig. 3).
-
Using
pressure-depth plots in PPG-MWE (pounds per gallon of mud weight equivalent) for calibrating the predicted values to the measured ones (Fig. 4).
Figure
1. The effective stress transformation model from
velocity
(on the left panel) to pore pressure(on the right panel). Notice the importance of defining the slope on the normal compaction trend (NCT) and the exponent X.
Figure
3. Two examples of breaking the normal compaction trend for the purpose
of calibration.
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