(664d) Mixed-Integer Nonlinear Programming Models for Line Pressure Optimization in Shale Gas Gathering Systems

Mixed-Integer Nonlinear Programming Models for Line Pressure Optimization in Shale Gas Gathering Systems

Markus G. Drouven¹ & Ignacio E. Grossmann²

Department of Chemical Engineering

Carnegie Mellon University

Pittsburgh, PA 15213, USA

 ¹mdrouven@cmu.edu, ²grossmann@cmu.edu

Abstract

 Shale gas gathering systems are characterized by a few key elements, namely: existing and prospective well pads, existing and prospective gathering pipelines of varying sizes, one or several compressors and a coupling link to a large-diameter, long-distance transmission pipeline. On every existent pad one or more shale wells actively produce natural gas which is then fed into gathering lines at varying rates over time. The shale gas gathering system itself is typically operated at relatively low pressures, ranging from 50-200 psi. Low line pressures allow producers to extract the most gas from their shale wells, since they create a large differential between the reservoir pressure and the wellhead pressure. In other words, as the line pressure in a gathering system increases, overall production typically decreases (Lee & Wattenberger, 1996; Boyan & Ghalambor, 2014). Since the reverse statement is true as well, upstream producers generally prefer to operate their gathering systems at the lowest possible line pressure.

 However, eventually the produced gas needs to be delivered to a transmission pipeline which will move the gas to major demand hubs. These transmission lines are operated by midstream companies at very high pressures between 900-1,200 psi in order to transport large quantities of natural gas over long distances. Therefore, it is up to the shale gas producer to overcome the pressure differential between the low-pressure gathering system and the high-pressure transmission line. This is typically accomplished through one or several compressors. Compressor stations allow upstream operators to produce the gas at low pressures, on the one hand, but still meet the transmission line’s pressure delivery requirements on the other hand. Due to the significant pressure differential that needs to be overcome by the compressor, and the considerable volumes of gas that are processed, compression expenses can be a major cost factor in the operation of shale gas gathering systems. Consequently, upstream producers struggle to balance two conflicting objectives: a) operating their gathering systems at low pressures and thereby increasing gas production, and b) raising line pressures so as to minimize compression expenses.

In this work we present a multiperiod mixed-integer nonlinear programming model to address the line pressure optimization problem in shale gas gathering systems. The problem at hand can be stated as follows. Within an active development area, an upstream operator is actively producing natural gas from a set of existing shale wells into an existing gas gathering system. This pipeline system delivers the produced gas to a compressor station which feeds into a long-distance, wide-diameter, high-pressure transmission line. Within the foreseeable future the producer wishes to open up additional prospective wells to maximize the utilization of the available gas gathering capacity.

Our work is concerned with: a) determining the optimal schedule to turn prospective wells in-line, also referred to as the “turn-in-line (TIL) schedule”, b) identifying the optimal pressure profile within the gas gathering network, and c) calculating the required compression power to deliver the gas into the interstate transmission network. The problem is complicated by the fact that as new wells are brought online, the production of previously producing wells is negatively affected. In other words, the increase in line pressure due to additional gas production curtails gas recovery from mature wells. This effect is particularly prominent due to the characteristically steep decline curves of new shale gas wells. Hence, the objective of this work is to determine the optimal “TIL” schedule, line pressure profile and compressor operation such that the net present value of the field development project is maximized.

We rely on a pressure-normalized decline curve model to quantify how line pressure variations impact the gas production of individual wells. The reservoir model itself is incorporated in a transmission optimization framework which rigorously evaluates pressure drops along pipeline segments. Moreover, we explicitly consider compression requirements to lift line pressure from gas gathering levels to setpoints dictated by transmission pipeline companies. Since the resulting optimization models are large-scale, nonlinear and nonconvex, we propose a solution procedure based on an efficient initialization strategy. Finally, we present a detailed case study and we show that the proposed optimization framework can be used effectively to manage line pressures in shale gas gathering systems by properly scheduling when, and how many, new wells are brought online.

References [1] Lee J, Wattenberger RA. Gas Reservoir Engineering. Society of Petroleum Engineers. 1996. [2] Boyan G, Ghalambor A. Natural Gas Engineering Handbook. Elsevier. 2014. [3] Drouven MG, Grossmann IE. Mixed-Integer Nonlinear Programming Models for Line Pressure Optimization in Shale Gas Gathering Systems. Journal of Petroleum Science and Engineering. Submitted for publication. 2017.