Stochastic programming models for optimal shale well development and refracturing planning under uncertainty

Abstract

In this work we present an optimization framework for shale gas well development and refracturing planning. This problem is concerned with if and when a new shale gas well should be drilled at a prospective location, and whether or not it should be refractured over its lifespan. We account for exogenous gas price uncertainty and endogenous well performance uncertainty. We propose a mixed‐integer linear, two‐stage stochastic programming model embedded in a moving horizon strategy to dynamically solve the planning problem. A generalized production estimate function is described that predicts the gas production over time depending on how often a well has been refractured, and when exactly it was restimulated last. From a detailed case study, we conclude that early in the life of an active shale well, refracturing makes economic sense even in low‐price environments, whereas additional restimulations only appear to be justified if prices are high. © 2017 American Institute of Chemical Engineers AIChE J, 2017

Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms

“…Tavallali et al [130] also combine well placement and control. The results of both Drouven et al [129] and Tavallali et al [130] highlight valuable insight into the well placement and control interrelationship obtained by combining well placement and control optimization. Adjoint optimization is finding increased use in coupled well placement and injection optimization.…”

“…They found that profitability of investments could be significantly improved by combining well location and surface gathering considerations. In recent work Drouven et al [129] optimize shell gas well placement and refracturing scheduling together. Tavallali et al [130] also combine well placement and control.…”

Shale gas pad development planning under price uncertainty

“…The models for shale gas development that consider uncertainty are relatively few. Drouven et al apply two‐stage stochastic programming in a moving horizon approach for optimal shale well development and refracturing planning under exogenous gas price uncertainty and endogenous well performance uncertainty. Gao and You develop a two‐stage stochastic mixed integer linear fractional programming (SMILFP) model to optimize the levelized cost of energy generated from shale gas under uncertainty of estimated ultimate recovery (EUR).…”

Integrated shale gas supply chain design and water management under uncertainty

“…Moreover, data driven or simulation based tools have been developed for the economic assessment of natural gas production from shale gas plays, including considerations regarding the optimal well‐pad layout . Furthermore, supply chain optimization models have also been proposed for shale gas development, for the corresponding water management problems, and for the integrated shale gas development and water management problem . Some of the aforementioned frameworks consider uncertainty in freshwater availability, water demand for hydraulic fracturing as well as wastewater production, gas production, and gas prices .…”

“…Furthermore, supply chain optimization models have also been proposed for shale gas development, for the corresponding water management problems, and for the integrated shale gas development and water management problem . Some of the aforementioned frameworks consider uncertainty in freshwater availability, water demand for hydraulic fracturing as well as wastewater production, gas production, and gas prices . Although significant progress has been achieved in the modeling, simulation, and optimization of shale gas development, further research efforts are needed towards the development of integrated supply chain models that deal with the uncertainties in a systematic way.…”