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Rapid Identification and Ranking of Reservoir
Flow Units, Happy Spraberry Field,
Garza County, Texas*
By
John Layman III1 and Wayne Ahr2
Search and Discovery Article #40144 (2005)
Posted March 1, 2005
*Adapted from extended abstract, entitled “Porosity Characterization Utilizing
Petrographic Image Analysis: Implications for Rapid Identification and Ranking
of Reservoir
Flow Units, Happy Spraberry Field, Garza County, Texas,” prepared
for presentation at AAPG International Conference & Exhibition, Cancun, Mexico,
October 24-27, 2004.
1Amerada Hess Corporation, Houston, TX
2Texas A&M University, College Station, TX ([email protected])
Abstract
Carbonate reservoirs may be heterogeneous and exhibit lateral and vertical
variations in porosity and permeability. New technology and an improved
understanding of carbonate reservoirs have led to more detailed reservoir
description, flow unit delineation, and flow unit ranking. Petrographic image
analysis (PIA), a relatively new method, was used to analyze the carbonate
porosity of the
reservoir
interval at Happy field, Garza County, Texas. The
reservoir
produces from depths of -4900 to -5100 feet and consists of Lower
Permian oolitic grainstones and packstones. Associated floatstones, rudstones,
and in situ Tubiphytes bindstones are also present in the interval.
Reservoir
pore
characteristics and their corresponding degrees of connectivity (“quality”) were
determined using standard petrography, PIA, core analyses, and mercury injection
capillary pressures. The PIA method enables rapid measurements of pore size,
shape, frequency of occurrence, and abundance. Common pore characteristics were
used to identify stratigraphic and
diagenetically
similar intervals, within
which four pore facies were observed. Pore facies were defined and ranked as to
quality by comparing PIA data with measured porosity, permeability, and, in a
limited number of samples, median pore throat diameters. Pore facies exhibiting
oomoldic and solution-enhanced interparticle porosity ranked best in quality.
Rocks with incomplete molds and dispersed interparticle pores ranked second;
rocks with mainly separate molds ranked third, and rudstones, floatstones, and
bindstones with dispersed separate vugs and matrix porosity ranked fourth. The
PIA technique is a viable and fast alternative to standard petrography. It
yields data that compares with petrophysical measurements and, when properly
used, is a valuable method for
reservoir
characterization in heterogeneous
carbonate pore systems.
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Introduction
This study tests the applicability of PIA as a tool for identifying
Study Area and Methods
Happy field is located in south central Garza County, Texas, on the
eastern shelf that flanks the Midland Basin (Figure
1). Data used in the study include core from five wells, 52
petrographic thin-sections, capillary pressure measurements, and
wireline log data. Cores were described for sedimentary structures,
constituent grains, and depositional fabric (Layman II, 2002).
Thin-sections were examined by standard petrographic methods for total
porosity, per abundance, pore types, grain constituents, and cements.
Wireline logs were used to calculate porosity on
Petrographic image analysis of carbonate pores has been used to predict
Stratigraphy and Lithology
The carbonate interval at Happy field is interpreted as Lower Clear Fork
Formation (lower Leonardian). This is time-equivalent to the basinal
Dean sandstone (Montgomery, 1998). Primary production is from a
grainstone shoal
Results
The types of data obtained from PIA studies include pore size, shape,
frequency, and abundance (total porosity). In addition, pores in each
sample were classified according to their geological origin. Total
porosity from PIA was compared to porosity values obtained from standard
petrographic methods, log calculations, and core analyses. The
comparisons showed that the accuracy of PIA estimates of porosity are
comparable to the other methods. Porosity histograms were constructed
from the pore data to assess all pore characteristics rapidly (Figure
3). Samples were then correlated to determine trends and patterns in
the pore data that defined pore facies of the
Pore facies are combinations of pore data that have predictable
Happy Spraberry field produces from heterogeneous, shallow-shelf carbonates where lateral and vertical variations in porosity and permeability are common. Porosity is predominantly a diagenetic overprint on depositional texture (grain-moldic in oolitic grainstones). Utilizing PIA as a method for characterizing carbonate reservoirs is a relatively new procedure. Data on pore characteristics is obtained much faster than standard petrographic methods.
Image analysis data were interpreted to identify 4 distinctive pore
facies which, in turn, are predictors of rock type, petrophysical
properties, and production characteristics. Image analysis was proven to
be a good substitute for more time-consuming methods for determining
porosity and provided results with accuracy comparable to results
obtained from core analyses, wireline log calculations, and standard
petrographic methods. The highest quality
AcknowledgmentsThis study was part of a Master’s Thesis at Texas A&M University. I would like to thank the members of my committee: Wayne Ahr, Tom Blasingame, and Steve Dorobek. I would also like to thank Bob Berg for substituting at my defense. I would also like to thank those who funded this research: AAPG Grant-in-Aid, Texas A&M University Graduate Fellowship, and the late Mr. Michel T. Halbouty for a generous scholarship.
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