(22e) Optimization Models for Shale Gas Development Planning: A Real-World Marcellus Shale Case Study
AIChE Annual Meeting
2016
2016 AIChE Annual Meeting
Computing and Systems Technology Division
CAST Director's Student Presentation Award Finalists
Sunday, November 13, 2016 - 4:46pm to 5:05pm
Optimization Models for Shale Gas Development
Planning:
A Real-World Marcellus Shale Case Study
Markus G. Drouven1 and Ignacio E. Grossmann2
Department of Chemical Engineering
Carnegie Mellon University
Pittsburgh, PA 15213
1mdrouven@cmu.edu, 2grossmann@cmu.edu
Abstract
The production of shale
gas from unconventional resource plays is transforming the energy landscape in the
United States. Advances in production technologies, notably the dual
application of horizontal drilling and hydraulic fracturing, allow the
extraction of vast deposits of trapped natural gas that, until recently, were
uneconomic to produce. The Energy Information Administration predicts that
shale gas will account for 50% of total U.S. natural gas production by 2040
[1]. Natural gas demand is also expected to increase in the electric power and
nearly all other industrial sectors. The future development of shale gas
resources requires an extensive expansion of the existing gas production,
transmission, and processing infrastructure. Virtually all stages of the shale
gas supply chain need to be expanded and upgraded to match the ever growing
natural gas supply and demand [2]. Since the necessary capital investments for
drilling rigs, pipelines, boosting stations and midstream processing facilities
are substantial, the long-term planning of upstream production and natural gas
transmission is a key challenge.
In this presentation we
address a real-world case study for which the general problem can be stated as
follows. Within a potential shale gas development area an upstream operator has
identified a set of candidate well pads from which shale gas may or may not be
extracted. To extract the gas the operator can develop, i.e., drill and
fracture a limited number of wells at every candidate pad. Ultimately, the
operator wishes to sell extracted gas at a set of downstream delivery nodes
which are typically located along interstate transmission pipelines. For this
purpose a gathering system superstructure has been identified. This
superstructure specifies all feasible, alternative options for laying out
gathering pipelines to connect candidate well pads with the given set of
delivery nodes. In addition, the superstructure indicates candidate locations
for compressor stations as well as the location of existing processing plants.
The long-term shale gas
development problem involves planning, design and strategic decisions. In terms
of planning decisions the operator needs to decide: a) where, when and how many
wells to drill at every candidate well pad, b) whether selected wells should be
shut-in and, if so, for how long, and c) how to allocate drilling rigs over
time. The design decisions involve: a) where to lay out gathering pipelines, b)
what size pipelines to install, c) where to construct compressor stations, and
d) how much compression power to provide. The upstream operators objective is
to determine the optimal development strategy by making the right planning and
design decisions such that the net present value is maximized.
In this work [3] we
present a real-world Marcellus Shale case study that was performed in close
collaboration with the EQT Corporation. EQT is one of the largest exploration
and production operators in the Appalachian Basin. Their business activities
include locating productive natural gas deposits, drilling wells to extract gas
and transporting gas through pipelines to transmission and distribution system.
The objective of this case study was twofold: (a) validate and refine the
proposed modeling framework and (b) attempt to quantify the economic potential
of mixed-integer optimization models for long-term shale gas development planning.
As part of a lookback
analysis the proposed model was applied to an existing gathering system in the
Appalachian Basin owned and operated by the EQT Corporation using real,
historic data. By comparing the development strategy proposed by the
optimization with the actual, historic development strategy, we are able to
demonstrate and quantify the economic potential of optimization tools for shale
gas development. Our findings suggest, in the past, development strategies were
primarily driven by trying to drill as many wells as possible at a given location and turning them in line as quickly as possible.
However, considering the characteristically steep decline curves of shale gas
wells we find that these development strategies led to gathering equipment
including pipelines and compressors being over-sized and therefore heavily
under-utilized over long periods of time.
Our optimization, on the
other hand, reveals that so-called return-to-pad operations appear much more
suitable and economically promising for shale gas development projects. The
idea behind return-to-pad operations is to drill and complete only a small
number of wells at a time, but then to return to the pad eventually to repeat
the process. This strategy allows upstream operators to size gathering
pipelines and compressor smaller and to keep them full, i.e., utilized, over
extended periods of time.
Our comprehensive
economic analysis reveals that return-to-pad operations and an increased
equipment utilization could have improved the profitability of this particular
development project by several million U.S. dollars. To the best of our
knowledge this is the first case study that provides such deep and realistic
insight into past and future shale gas development strategies in collaboration
with a major natural gas producer.
References
[1] U.S. Energy Information Administration
(EIA). Annual Energy Outlook with Projections to 2040. April 2013.
[2] Goellner, J.
F. Expanding the Shale Gas Infrastructure. AIChE CEP August 2012, 49-52.
[3] Drouven, M. G.; Grossmann, I. E.
Multi-Period Planning, Design and Strategic Models for Long-Term
Quality-Sensitive Shale Gas Development. AIChE J. 2016 (accepted for
publication).