American Oil and Gas Reporter - December 2016 - 56

SpecialReport: Well Stimulation & Completion Technology
0.85 correlation coefficient on a population
of 30 plus wells.
Initially, this technique excluded a
number of the 3-D attributes derived
solely from the seismic inversion process,
which were extracted later at the wellbore
and were combined to improve the correlation in instances when the logs alone
did not provide sufficiently high-quality
correlations. This also demonstrates that
no single factor drives well production,
but rather a combination of variables.
The second validation step represents
a process of reviewing actual results

versus prognostications from the production attribute response. Initial field test
validation was performed against a population of blind test control wells (validation wells) available for comparison
soon after the workflow had been developed. Importantly, while the locations of
the validation wells were within the earth
model area of interest, landing points
were not optimized utilizing the production
attribute, enabling a sufficient sampling
of lower and higher production attribute
values.
Over time, additional well results,

FIGURE 5
Example of Standard Wellbore
And Earth Model Optimized Landing Points

Low

High

90-day Oil Cumulative (BO)

Standard
Wellbore

Select Landing
Point

1
3

Geosteering
(stay in zone)

2
1

2
Frac Design
& Spacing
3

Earth Model
Optimized Wellbore

FIGURE 6
Standard Wellbore and Earth Model Optimized Landing Points
Overlain on Simplified Dipole Sonic Log
F.G.
GR

Lith

LP1:
Standard
Wellbore

Importance to Landing Point
Low

High

OOIP
LP2

LP1

Frac Grad
LP1

LP2:
Earth
Model
Optimized

LP2

Brittleness
LP2

LP1
Clay
LP1

LP2

Natural
Fractures
LP1

56 THE AMERICAN OIL & GAS REPORTER

LP2

more recent empirical data, and new interpretations have revealed further complexities related to production drivers.
The workflow adopted allows for new
findings to be included.
Development Planning
Laredo's earth model has been integrated fully into development planning
and operational execution workflows.
This allows efficient comparisons of development options while considering producing wells (both vertical and horizontal),
along with mechanical frac barriers present
within the stratigraphy.
Once a particular area of the field has
been selected for development, the potential across all zones is reviewed to determine the vertical and spatial distribution
of landing points. The highest three- and
six-month (if available) predicted production from various landing points is
reviewed and the values are entered into
economic valuations. Given that different
zones at different depths have variable
drilling and completion considerations,
the earth model results provide timely
information for well planning purposes.
Figure 5 is a simple example of
optimizing landing points with the earth
model 3-D production attibute. This case
uses two stand-alone wellbores separated
by approximately one-half mile. The
"standard wellbore" demonstrates an approach to selecting the landing point
based on logs alone (proximal dipole
sonic logs were available predrill to assist
in this decision process).
Figure 6 shows the two landing points
superimposed on a simplified dipole sonic
log display. The STB40 curve represents
a 200-foot running window average of
stock-tank OOIP per 40 acres. Qualitative
landing point considerations are shown
and their relative importance is noted.
Without the production attribute, the high
stock-tank OOIP and reasonable rock
properties (including clay content and
frac gradient) would strongly influence
selecting the standard wellbore landing
point.
The earth model-optimized landing
point is not necessarily obvious when
one is interpreting log data alone. The
additional attributes in the earth model
workflow are key to revealing landing

American Oil and Gas Reporter - December 2016

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