Page 323 - Fundamentals of Gas Shale Reservoirs
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INTRODUCTION    303

            TAbLE 14.1  Tools used to estimate reserves
                                                                       Conventional
            Method       Advantage            Disadvantage             reservoir           Unconventional reservoir
            Analogy      •  Best in blanket sands  The large number of variables   Can be applied in both conventional and unconventional
                         •  Best prior to       and parameters causes high   assets
                           production           degree of uncertainty
            Volumetric   •  Any stage of      Has uncertainties of     Accurate in blanket   Used only when no wells
              method       depletion          •  recovery factor (RF)    reservoir           have been drilled
                         •  Best prior to     •  actual drainage area
                           production
            Material     Best between 10 and   Requires:               Accurate in depletion   •  Should never be used
              balance      70% depletion      •  accurate average pressure  drive reservoir  •  Average pressure cannot
                                              •  reservoir fluid properties                 be measured accurately
            Decline curve   •  Simple, easy to apply  Requirements difficult to met  Hyperbolic (small b)   Must use hyperbolic decline:
              analysis   •  Less data required   •  Boundary dominated flow  or exponential   •  CBM: b = 0–0.5
                           (only rate‐time)   •  Unchanging drainage area  decline usually   •  Shale gas and tight gas:
                         •  Best with long    •  Fixed skin factor       accurate           b may be larger than 1
                           production history  •  “b” value constant and                   •  Use best‐fit “b” until
                         •  Quick               should lie between 0 and 1                  predetermined minimum
                                              •  Can overestimate reserves                  decline rate reached, then
                                                                                            impose exponential decline
                                                                                           •  Set “b” to proper “terminal
                                                                                            value”
            Reservoir    •  Best with data rich   •  Needs good history match  Used to simulate field  Used to simulate individual
              simulation   wells              •  Requires much time, costly                  wells
                         •  In conjunction with
                           other methods any
                           time



            Spivey, 1996). Reservoir simulation coupled with stochastic   published by Warren and Root (1963) and Kazemi (1969).
            methods (e.g., Monte  Carlo simulation) has  provided an   Semianalytical  solutions  for  hydraulically fractured
            excellent means to predict production profiles for a wide   horizontal wells in fractured reservoirs have been published
            variety of reservoir characteristics and producing conditions.   (Medeiros et al., 2008). PMTx 2.0 (2012), with a number of
            The uncertainty is assessed by generating a large number of   modeling options, such as a transient dual‐porosity reser-
            simulations, sampling from distributions of uncertain   voir model (Kazemi, 1969), is an analytical unconventional
            geologic, engineering, and other important parameters. This   gas reservoir simulator designed to quickly and easily
            topic has been an object of study for some time in conven-  model single‐well, single‐phase, gas production based on
            tional reservoirs (MacMillan et al., 1999; Nakayama, 2000;   near‐wellbore reservoir performance under specified well
            Sawyer et al., 1999). However, few applications to unconven-  completion scenarios. One of the important applications of
            tional reservoirs can be found in the literature. Oudinot et al.   PMTx 2.0 is to estimate ultimate gas recovery for horizontal
            (2005) coupled Monte Carlo simulation with a fractured res-  wells with transverse fractures in a rectangular shale gas
            ervoir simulator, COMET3, to assess the EUR in coalbed   reservoir.
            methane reservoirs. Schepers et al. (2009) successfully applied
            this Monte Carlo COMET3 procedure to forecast EUR for the   14.1.7  Economic Analysis
            Utica Shale.
                                                                 Almadani (2010) presented a methodology to determine the
                                                                 percentage of TRR that is economically recoverable from
            14.1.6  Analytical Models
                                                                 the Barnett Shale as a function of gas price and finding and
            Given the complex nature of hydraulic fracture growth, the   development costs (F&DC). For ERR he applied economic
            extremely low permeability of the matrix rock in many   criteria of minimum 20% internal rate of return (IRR) and
            shale  gas  reservoirs,  and  the  predominance  of  horizontal   maximum 5‐year payout to recover the initial investment,
            completions, reservoir simulation is often the preferred   which are hurdles sometimes used by investors in the oil and
            method to predict and evaluate well performance. Analytical   gas industry. The author suggested that wells that do not pay
            solutions for fluid flow in naturally fracture reservoirs were   out in 5 years are not good investment.
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