Conditioning the Estimating Ultimate Recovery of Shale Wells to Reservoir and Completion Parameters
Author(s) -
Maher Alabboodi,
Shahab D. Mohaghegh
Publication year - 2016
Publication title -
spe eastern regional meeting
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.119
H-Index - 1
DOI - 10.2118/184064-ms
Subject(s) - completion (oil and gas wells) , oil shale , petroleum engineering , production (economics) , exponential function , geology , environmental science , statistics , soil science , hydrology (agriculture) , mathematics , geotechnical engineering , economics , paleontology , mathematical analysis , macroeconomics
Oil and gas production from shale has increased significantly in the United States. Forecasting production and estimating ultimate recovery (EUR) using Decline Curve Analysis (DCA) is performed routinely during development and planning. Different methods to calculate EUR have been used in the industry (Hyperbolic Decline, Power Law, Stretched Exponential, Dung’s and Tail-end Exponential). Traditionally, the decline curve analysis method by Arps (1945) was considered to be the best common tool for estimating ultimate recovery (EUR) and reserves. However, the Arps’ equations over estimate of reserves when they are applied to unconventional reservoirs. Multiple modifications to Arp’s method have been proposed in order to extend the applicability of DCA to forecast production and estimate the recovery from shale wells. Decline Curve Analysis, including all its flavors that recently have surfaced, is essentially a curve fitting technique that does not take into account reservoir, completion and production characteristics when estimating EUR. In this paper, we compare the impact and influence of field measurements (reservoir, completion and production characteristics) on the estimations made by different DCA techniques. Since these new DCA techniques give rise to different EURs does it mean that they are giving more weight to one set of parameters at the expense of other sets (albeit, unintentionally)? We perform four different types of DCA and calculate EUR for more than 200 wells in one asset in Marcellus shale. Then using data-driven analytics, we examine the impact of reservoir characteristics (porosity, total organic carbon, net thickness and water saturation), completion characteristics (number of stages, amount of fluid and proppant used per stage, injection rates and pressure), and operational constraints (well-head pressure) on the EUR calculated by each of the DCA techniques. The question we are trying to answer is whether the use of a particular DCA technique translates into the emphasis of a certain group of parameters. Introduction Hydrocarbon production from unconventional shale gas reservoirs has become more common in the past decade. Therefore, prediction of hydrocarbon recovery or estimated ultimate recovery (EUR) for these reservoirs throughout the life of wells is considered the main step in development planning. Decline curve analysis technique is the most popular graphical-mathematical method in the industry used to calculate EUR. The traditional decline curve technique shows unreasonable results when applied in unconventional reservoirs because of the complexities in petrophysical and mechanical properties of these reservoirs.
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