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.
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Basic Q & A,
Data (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 functions and how does this relate to lithology?
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
In Cored
How Does this Ultimately Affect Net Pay? (Figures 16 and 17)
Results from cored
Application to Static Modeling
Serpentina West Model Figures 18-22
Goals
Results
Topacio South 2 (Figures 23-24)
Facies and |