In 1997, Rogner published a paper containing an estimate of the natural gas in place in unconventional reservoirs for 11 world regions. Rogner's work was assessing the unconventional gas resource base, and is now considered to be very conservative. Very little is known publicly about technically recoverable unconventional gas resource potential on a global scale. Driven by a new understanding of the size of gas shale resources in the United States, we estimated original gas in place (OGIP) and technically recoverable resource (TRR) in highly uncertain unconventional gas reservoirs, worldwide. We evaluated global unconventional OGIP by (1) developing theoretical statistic relationships between conventional hydrocarbon and unconventional gas; (2) fitting these relationships to North America publically available data; and (3) applying North American theoretical statistical relationships to evaluate the volume of unconventional gas resource of the world. Estimated global unconventional OGIP ranges from 83,300 (P10) to 184,200 (P90) Tcf. To assess global TRR from unconventional gas reservoirs, we developed a computer program that we call Unconventional Gas Resource Assessment System (UGRAS). In the program, we integrated a Monte Carlo technique with an analytical reservoir simulator to estimate the original volume of gas in place and to predict production performance. We used UGRAS to evaluate the probabilistic distribution of OGIP, TRR and recovery factor (RF) for the most productive unconventional gas formations in the North America. The P50 of recovery factor for shale gas, tight sands gas and coalbed methane is 25%, 79% and 41%, respectively. Finally, we applied our global OGIP assessment and these distributions of recovery factor gained from our analyses of plays/formations in the United States to estimate global technically recoverable unconventional gas resource. Global technically recoverable unconventional gas resource is estimated from 43,000 (P10) to 112,000 (P90) Tcf.

New decline curve models have been developed to overcome the boundary-dominated flow assumption of the basic Arps’ models, which restricts their application in ultra-low permeability reservoirs exhibiting long-duration transient flow regimes. However, these new decline curve analysis (DCA) methods are still based only on production rate data, relying on the assumption of stable flowing pressure. Since this stabilized state is not reached rapidly in most cases, the applicability of these methods and the reliability of their solutions may be compromised. In addition, production performance predictions cannot be disassociated from the existing operation constraints under which production history was developed. On the other hand, DCA is often carried out without a proper identification of flow regimes. The arbitrary application of DCA models regardless of existing flow regimes may produce unrealistic production forecasts, because these models have been designed assuming specific flow regimes. The main purpose of this study was to evaluate the possible benefits provided by including flowing pressures in production decline analysis. As a result, it have been demonstrated that decline curve analysis based on pressure-normalized rates can be used as a reliable production forecasting technique suited to interpret unconventional wells in specific situations such as unstable operating conditions, limited availability of production data (short production history) and high-pressure, rate-restricted wells. In addition, pressure-normalized DCA techniques proved to have the special ability of dissociating the estimation of future production performance from the existing operation constraints under which production history was developed. On the other hand, it was also observed than more consistent and representative flow regime interpretations may be obtained as diagnostic plots are improved by including MBT, pseudovariables (for gas wells) and pressure-normalized rates. This means that misinterpretations may occur if diagnostic plots are not applied correctly. In general, an improved forecasting ability implies greater accuracy in the production performance forecasts and more reliable reserve estimations. The petroleum industry may become more confident in reserves estimates, which are the basis for the design of development plans, investment decisions, and valuation of companies’ assets.