SPE-180140-MS Shale Reserve Forecasting - Model Consistency and Uncertainty Curtis Hays Whitson, NTNU; Carolina Coll, BG Group; Mohamad Majzoub Dahouk, and Aleksander Oma Juell, Petrostreamz AS Copyright 2016, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Europec featured at 78th EAGE Conference and Exhibition held in Vienna, Austria, 30 May–2 June 2016. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright. Abstract Three general categories of modeling are traditionally used to provide shale reserve forecasting – (1) decline curve analysis (DCA), (2) rate-time analysis (RTA), and (3) numerical model history matching (HM). The focus of this paper is aligning each of the three modeling approaches to ensure maximum consistency in terms of fundamental reservoir description, including (but not limited to) initial fluid in place, reservoir rock properties, PVT, well completion factors, fracture area and conductivity, well controls, and definition of infinite-acting and boundary-dominated flow regimes. The HM model ap- proach, though more rigorous, is time consuming and cannot be used for the hundreds of wells in a typical shale field. We recommend, as have others, that history-matched numerical models be used to help calibrate RTA and DCA models in a consistent manner for all wells. Once a consistent model framework is achieved, reserve forecasting can be better understood by regulators, engineering and reserve teams within the operating company and their partners. Furthermore, a consistent modeling framework can provide more reliable uncertainty analysis to establish probabilistic reserves estimates in terms of P90-P50-P10 values (1P-2P-3P). Modeling methods used in forecasting shale reserves are based on production data that includes rates and pressures. DCA applies the boundary-dominated methods such as Arps, where multiple time regions are used to capture infinite-acting and boundary-dominated flow. RTA uses dimensionless pressure and rate solutions applicable to horizontal wells with multiple fractures, including superposition, pseudopres- sure and pseudotime. Numerical models solve the complex set of differential equations describing multiphase fluid flow using a properly-selected grid refinement (e.g. near fractures) and, in some cases, a dual porosity/dual permeability treatment of fracture-matrix interaction. Introduction For the past decade an explosive increase has been seen in North American production of gas and light oil from shale and ultra-tight formations using horizontal wells with multiple hydraulic fractures (HZMF). This regional production increase is a product of thousands of new wells, each having a similar multi-cycle production performance. Initial high rates (gas5-10 MMscf/D and/or oil1,000 STB/D) last for months or years during which flowing pressures continuously decrease. This is followed by several years of higher decline rate, though still with substantial rates (gas500 Mscf/D and/or oil100 STB/D).