Click to view poster in PDF format (~6.6 mb).
PSUse of High-Resolution Core Description Data to Risk Net Pay from Log-Based Petrofacies for Thinly Bedded Deepwater Channel Complexes, Zafiro Field, Equatorial Guinea
By
T.C. Lukas1 and P. Schwans2
Search and Discovery Article #40248
Posted July 30, 2007
*Adapted from poster presentation at AAPG Annual Convention, Long Beach, California, April 1-4, 2007
1Consultant, Houston, TX ( [email protected] )
2Devon Energy, Houston, TX ( [email protected] )
Log-based facies or petrofacies contain thin beds at
or below log-resolution. Individual beds range from 2 – 0.01 feet. As a result
of thickness variations and stacking densities, estimates of thin bed net pay
are associated with significant uncertainty. Cores from Zafiro Field, Equatorial
Guinea, were used
to define thin-bed types and the ranges of uncertainties
associated with the beds identified via logs and cores.
The
Zafiro Field of Equatorial Guinea comprises a series of stacked channel
complexes of Miocene-Pliocene age deposited in the mid to lower slope position
of the Niger Delta. Thin bed environments in channel complexes include crevasse
splays, avulsion related lobes, lobes associated with overbank channels, levees,
and indeterminate remnants of near-channel overbank. High-resolution core
description data (100 samples/ft) from proximal to distal overbank deposits were
compared to log-based petrofacies computations. Data from the two methods were
compared as a function of hydrocarbon saturation, bed thickness, lithology, and
grain size and used
to condition the computations. This was compared to the pay
computed and predicted from the petrofacies probability curves. A set of
confidence levels are applied to a range of So cutoffs to better define the
uncertainty range. The described approach allows better benchmarking and risking
of log-based thin bed calculations and can be
used
in geostatic models.
uFacies & petrophysical modeling
uFacies & petrophysical modeling
uFacies & petrophysical modeling
uFacies & petrophysical modeling
uFacies & petrophysical modeling
uFacies & petrophysical modeling
uFacies & petrophysical modeling
uFacies & petrophysical modeling
uFacies & petrophysical modeling
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Basic Q & A, Data Analysis, and Data Products (Figures 1-3)
Goals, Evaluation, Description, and Comparison (Figures 4-10)
Petrofacies Probabilities for Thin Beds (ISS) How Do Petrofacies Probabilities for Thin beds (ISS) Relate to Possible Pay as a Function of:
How Do These Relationships:
What are the effects of changing the
probability
Zafiro-3 (Figures 11 and 12)
Opalo-2 (Figures 13 and 14)
Prediction—Petrofacies and Pay
How Much of the Predicted Petrofacies for Thin beds (ISS) is Valid by Core Description at a Specified Probability for a Particular So?
There are several ways to answer this question, using core description as the Benchmark. The most pertinent uses calibration of thin beds as predicted by ISS probability curves to pay valid by core description, for use in uncored wells.
In Cored Wells, for a Given Set of ISS Probabilities and So Values, What % of ISS Is Likely to Be Pay? (Figure 15)
How Does this Ultimately Affect Net Pay? (Figures 16 and 17)
Results from cored wells provide these answers; as So increases, particularly for shaly thin beds, the percentage of ISS valid by core description expressed as a function of net pay, and ultimately gross, decreases.
Application to Static Modeling
Serpentina West Model Figures 18-22
Goals
Results
Topacio South 2 (Figures 23-24)
Facies and Petrophysical Modeling |