Probabilistic Assessment of World Recoverable Shale Gas Resources

Abstract

Many shales previously thought of as only source rocks are now recognized as self-sourcing reservoirs that contain large volumes of natural gas and liquid hydrocarbons that can be produced using horizontal drilling and hydraulic fracturing. However, shale gas resources and development economics are uncertain, and these uncertainties beg for a probabilistic solution. Our objective was to probabilistically determine the distribution of technically recoverable resources (TRR) and shale original gas in place (OGIP) in highly uncertain and risky shale gas reservoirs for seven world regions. To assess technically recoverable resources, we used the distribution of recovery factors from shale gas reservoirs. We developed a software, Unconventional Gas Resource Assessment System (UGRAS), which integrates Monte Carlo simulation with an analytical reservoir simulator to establish the probability distribution of OGIP and TRR. We used UGRAS to evaluate the most productive shale gas plays in the United States, including the Barnett, Eagle Ford, Marcellus, Fayetteville, and Haynesville shales, and derived a representative distribution of recovery factors for shale gas reservoirs. The recovery factors for the five shale gas plays follow a general Beta distribution with a mean value of 25%. Finally, we extended the distribution of recovery factors gained from our analyses of shale gas plays in the U.S. to estimate technically recoverable shale-gas resources for the seven world regions. Total technically recoverable shale gas resources are estimated to range from 4,000 Tcf (P90) to 24,000 Tcf (P10). UGRAS is a robust tool that may be used to evaluate and rank shale-gas resources worldwide. This work provides important statistics for the five most productive shale-gas plays in the United States. Results of this work verify the existence of significant technically recoverable shale gas resources worldwide and can help industry better target its exploitation efforts in shale-gas plays.

Workflow for Probabilistic Resource Estimation: Jafurah Basin Case Study (Saudi Arabia)

“…We used one probability density function (pdf) for oil condensate recovery and one for gas recovery (Figure 10), as applicable to a wet gas product range in various ratios weighed by the GOR. The conventional curves were based on conference data compiled by Laherrere [51], which were previously used to argue unconventional resources may have similar distributions-but shifted toward the left in the plot of cumulative recovery probabilities [44,45]. We found that the conventional oil recovery factors fit well to a normal distribution, with a mean at 28% and standard deviation of about 14%.…”

A selection methodology of flowback treatment technologies and water reuse in hydraulic fracturing in source rocks – a strategy to reduce the environmental impacts in Colombia

“…A foreign formation similar to a Colombian formation must be identified in this case, aimed at correlating the physic chemical features of the flowback. According to data as shown in Dong et al (2014), Lesar (2011), U.S. Energy Information Administration (2011), Murphy (2013) formation located in the Magdalena Valley (VMM) and the Shale Eagle Ford, showed similarities in their petro physic and geologic features; as shown in Table 2. In order to establish the similarities between these two formations the following parameters were taken into account: permeability, porosity, TOC (Cerón,, Walls & Diaz, 2013), type of hydrocarbons, type of kerogene, temperature and vitrinite reflectance (Ro).…”

“…Source:(Dong et al, 2014;Lesar, 2011; U.S. Energy Information Administration, 2011;Murphy, 2013). Formation data of La Luna shown in the Table, is the result of the comprehensive characterization of the bottom interval laboratory in La Luna well in theICP, 2012 …”

Development of Production-Forecasting Model Based on the Characteristics of Production Decline Analysis Using the Reservoir and Hydraulic Fracture Parameters in Montney Shale Gas Reservoir, Canada

“…Input parameters for the base reservoir model (modified from[16,17,[19][20][21][22][23][24][25][26]). …”