American Oil and Gas Reporter - November 2017 - 48

SpecialReport: Oil & Gas Computing
Ford Shale zone.
The analysis of the probability distribution gives good
insights into prospect uncertainty and seismic data reliability
for prediction. Shale geoscientists and drilling engineers now
have a lithofacies model to correlate with other field data and to
optimize well plans. This technology should be applied to all
shale resource plays where lithofacies heterogeneities directly
impact hydraulic fracturing success.
Optimizing Shale Production
Predictive analytics technology is just as critical to apply
during the production life-cycle as it is during exploration and
development. Not only must operators ensure they are drilling
in the right location, but they must avoid production deferral
and maximize the life of the field by producing optimally from
the reservoir.
Leadership in today's unconventional oil and gas environment
requires skilled management of ever-increasing volumes of
data. The data are analyzed by expert asset teams that alert the
business to production challenges and offer solutions using
state-of-the-art methods. Production issues still are detected
after the fact, however, and the ability to provide solutions is
often hampered by missing information. Advanced workflows
requiring rich datasets and incorporating reservoir physicsbased predictive analytics have been considered too complex,
time-consuming and impractical.
Optimized production operations require knowledge of critical
parameters such as flow rate, pressure, temperature and composition from the reservoir to the surface. Many of these parameters,
however, go unmeasured because of both technical and cost
constraints. The less information available, the more we must
rely on simplified approaches to analysis and design, risking
overdesign, rework and deferred production.
Numerical reservoir simulation is an approach that many
operators are using to predict well performance. While this is a
mature technology that uses production data to enrich datasets
FIGURE 6
Most Probable Facies
Of Lower Eagle Ford Shale Zone

48 THE AMERICAN OIL & GAS REPORTER

and predict future performance, the method is time consuming
and resource intensive. Proxy and statistical models alleviate
some of these issues, but reintroduce the risk involved in
ignoring subsurface physics.
These problems can be eliminated with a proprietary advanced
mathematics engine. The newly introduced solution is a fast,
reservoir physics-based predictive analytic solution that helps
solve production problems in unconventional plays before they
arise. It integrates field data with production and reservoir engineering fundamentals and cloud-based functionalities to enrich
production datasets and forecast future performance from the
reservoir to the well to the surface.
Complex fluid movements around multifractured horizontal
wells are simulated rigorously. Hydraulic fracture models can
be oriented and heterogeneous, and include complex structures
(Figure 7). Once the fracture scenario is defined, future flow
predictions can be computed in a few minutes without the need
for special computational infrastructure. The speed of the calculation (which is as accurate as traditional, slower approaches)
allows flow predictions for the first time to be used during realtime production operations to make day-to-day changes. In addition, it enables operators to perform scenario testing during
the design phase to decide how they should fracture the well.
As an example, these calculations make it possible to more
accurately determine the flow regime inside the well bore and
predict the onset of liquid loading, which can be debilitating to
production. Additionally, the analysis can help determine the
optimal operation point for artificial lift and ensure maximum
recovery without inappropriate pressure drawdown in the well.
FIGURE 7
Hydraulic Fracture Modeling Example
From New Cloud-Based Solution

American Oil and Gas Reporter - November 2017

Table of Contents for the Digital Edition of American Oil and Gas Reporter - November 2017