Analysis of Effective Porosity and Effective Permeability in Shale-Gas Reservoirs With Consideration of Gas Adsorption and Stress Effects

SPE Journal ◽  
2017 ◽  
Vol 22 (06) ◽  
pp. 1739-1759 ◽  
Author(s):  
Y.. Pang ◽  
M. Y. Soliman ◽  
H.. Deng ◽  
Hossein Emadi
Keyword(s):  
Pore Pressure ◽  
Shale Gas ◽  
Gas Adsorption ◽  
Effective Porosity ◽  
Gas Production ◽  
Gas Reservoirs ◽  
Adsorption Effect ◽  
Shale Gas Reservoirs ◽  
Porosity And Permeability ◽  
Stress Dependent

Summary Nanoscale porosity and permeability play important roles in the characterization of shale-gas reservoirs and predicting shale-gas-production behavior. The gas adsorption and stress effects are two crucial parameters that should be considered in shale rocks. Although stress-dependent porosity and permeability models have been introduced and applied to calculate effective porosity and permeability, the adsorption effect specified as pore volume (PV) occupied by adsorbate is not properly accounted. Generally, gas adsorption results in significant reduction of nanoscale porosity and permeability in shale-gas reservoirs because the PV is occupied by layers of adsorbed-gas molecules. In this paper, correlations of effective porosity and permeability with the consideration of combining effects of gas adsorption and stress are developed for shale. For the adsorption effect, methane-adsorption capacity of shale rocks is measured on five shale-core samples in the laboratory by use of the gravimetric method. Methane-adsorption capacity is evaluated through performing regression analysis on Gibbs adsorption data from experimental measurements by use of the modified Dubinin-Astakhov (D-A) equation (Sakurovs et al. 2007) under the supercritical condition, from which the density of adsorbate is found. In addition, the Gibbs adsorption data are converted to absolute adsorption data to determine the volume of adsorbate. Furthermore, the stress-dependent porosity and permeability are calculated by use of McKee correlations (McKee et al. 1988) with the experimentally measured constant pore compressibility by use of the nonadsorptive-gas-expansion method. The developed correlations illustrating the changes in porosity and permeability with pore pressure in shale are similar to those produced by the Shi and Durucan model (2005), which represents the decline of porosity and permeability with the increase of pore pressure in the coalbed. The tendency of porosity and permeability change is the inverse of the common stress-dependent regulation that porosity and permeability increase with the increase of pore pressure. Here, the gas-adsorption effect has a larger influence on PV than stress effect does, which is because more gas is attempting to adsorb on the surface of the matrix as pore pressure increases. Furthermore, the developed correlations are added into a numerical-simulation model at field scale, which successfully matches production data from a horizontal well with multistage hydraulic fractures in the Barnett Shale reservoir. The simulation results note that without considering the effect of PV occupied by adsorbed gas, characterization of reservoir properties and prediction of gas production by history matching cannot be performed reliably. The purpose of this study is to introduce a model to calculate the volume of the adsorbed phase through the adsorption isotherm and propose correlations of effective porosity and permeability in shale rocks, including the consideration of the effects of both gas adsorption and stress. In addition, practical application of the developed correlations to reservoir-simulation work might achieve an appropriate evaluation of effective porosity and permeability and provide an accurate estimation of gas production in shale-gas reservoirs.

scholarly journals Investigation of the Main Factors During Shale-gas Production Using Grey Relational Analysis

2016 ◽  
Vol 9 (1) ◽  
pp. 207-215 ◽  
Author(s):  
Hongling Zhang ◽  
Jing Wang ◽  
Haiyong Zhang
Keyword(s):  
Shale Gas ◽  
Gas Production ◽  
Gas Reservoirs ◽  
Fracture Conductivity ◽  
Matrix Permeability ◽  
Shale Gas Reservoirs ◽  
Main Factors ◽  
Grey Relational ◽  
The Impact ◽  
Half Length

Shale gas is one of the primary types of unconventional reservoirs to be exploited in search for long-lasting resources. Production from shale gas reservoirs requires horizontal drilling with hydraulic fracturing to achieve the most economic production. However, plenty of parameters (e.g., fracture conductivity, fracture spacing, half-length, matrix permeability, and porosity,etc) have high uncertainty that may cause unexpected high cost. Therefore, to develop an efficient and practical method for quantifying uncertainty and optimizing shale-gas production is highly desirable. This paper focuses on analyzing the main factors during gas production, including petro-physical parameters, hydraulic fracture parameters, and work conditions on shale-gas production performances. Firstly, numerous key parameters of shale-gas production from the fourteen best-known shale gas reservoirs in the United States are selected through the correlation analysis. Secondly, a grey relational grade method is used to quantitatively estimate the potential of developing target shale gas reservoirs as well as the impact ranking of these factors. Analyses on production data of many shale-gas reservoirs indicate that the recovery efficiencies are highly correlated with the major parameters predicted by the new method. Among all main factors, the impact ranking of major factors, from more important to less important, is matrix permeability, fracture conductivity, fracture density of hydraulic fracturing, reservoir pressure, total organic content (TOC), fracture half-length, adsorbed gas, reservoir thickness, reservoir depth, and clay content. This work can provide significant insights into quantifying the evaluation of the development potential of shale gas reservoirs, the influence degree of main factors, and optimization of shale gas production.

Study Evaluates Fracturing Interference for Multiwell Pads in Shale Gas Reservoirs

2021 ◽  
Vol 73 (08) ◽  
pp. 67-68
Author(s):  
Chris Carpenter
Keyword(s):  
Hydraulic Fracturing ◽  
Shale Gas ◽  
Technical Conference ◽  
Gas Production ◽  
Gas Reservoirs ◽  
Well Drilling ◽  
Recovery Potential ◽  
Shale Gas Reservoirs ◽  
Well Spacing ◽  
Southwest Region

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 201694, “Interwell Fracturing Interference Evaluation of Multiwell Pads in Shale Gas Reservoirs: A Case Study in WY Basin,” by Youwei He, SPE, Jianchun Guo, SPE, and Yong Tang, Southwest Petroleum University, et al., prepared for the 2020 SPE Annual Technical Conference and Exhibition, originally scheduled to be held in Denver, Colorado, 5–7 October. The paper has not been peer reviewed. The paper aims to determine the mechanisms of fracturing interference for multiwell pads in shale gas reservoirs and evaluate the effect of interwell fracturing interference on production. Field data of 56 shale gas wells in the WY Basin are applied to calculate the ratio of affected wells to newly fractured wells and understand its influence on gas production. The main controlling factors of fracturing interference are determined, and the interwell fracturing interacting types are presented. Production recovery potential for affected wells is analyzed, and suggestions for mitigating fracturing interference are proposed. Interwell Fracturing Interference Evaluation The WY shale play is in the southwest region of the Sichuan Basin, where shale gas reserves in the Wufeng-Longmaxi formation are estimated to be the highest in China. The reservoir has produced hydrocarbons since 2016. Infill well drilling and massive hydraulic fracturing operations have been applied in the basin. Each well pad usually is composed of six to eight multifractured horizontal wells (MFHWs). Well spacing within one pad, or the distance between adjacent well pads, is so small that fracture interference can occur easily between infill wells and parent wells. Fig. 1 shows the number of wells affected by in-fill well fracturing from 2016 to 2019 in the basin. As the number of newly drilled wells increased between 2017 and 2019, the number of wells affected by hydraulic fracturing has greatly increased. The number of wells experiencing fracturing interaction has reached 65 in the last 4 years at the time of writing.

Evaluation of free porosity in shale gas reservoirs (Roseneath and Murteree formations case study)

2012 ◽  
Vol 52 (1) ◽  
pp. 603
Author(s):  
Maqsood Ahmad ◽  
Ali Hussain ◽  
Reuben Koo ◽  
Hoang Nguyen's ◽  
Manouchehr Haghighi
Keyword(s):  
Shale Gas ◽  
Effective Porosity ◽  
Gas Reservoirs ◽  
Sem Images ◽  
Intergranular Porosity ◽  
Core Samples ◽  
Mercury Injection ◽  
Shale Gas Reservoirs ◽  
Carbonaceous Shales ◽  
Very High

Organically rich shale rocks represent a voluminous, long-term, global source of natural gas and could be referred to as shale gas. Unlike conventional gas reservoirs, shale gas reservoirs have very low effective porosity and permeability. Therefore, an evaluation of porosity in such a tight rock is a challenge. The Roseneath and Murtree shale formations in the Cooper Basin are believed to be potential shale gas reservoirs in SA. Core samples of Murteree and Roseneath carbonaceous shales from the Della–4 and Moomba–46 wells were collected to measure interstitial and intergranular porosity in these prospective shale gas reservoirs in the Nappamerri Trough. After initial preparation, the shale core samples were investigated to determine the pore size classification and effective free porosity using the mercury injection capillary pressure technique (MCIP). The focused ion beam/scanning electron microscopy (FIB/SEM) technique was then employed to obtain micro and nano scale images of the core samples. Then, helium porosimetry was used on the samples to measure their effective porosity. Finally, the pyknometry method was used on the crushed samples to measure their total intergranular porosity. MICP techniques revealed that the samples were mainly comprised of meso-porosity, with the pore throat diameters between 2–50 nanometres and an effective porosity of less than 2%. Helium porosimetry also showed an average porosity of less than 2%. Liquid pyknometry revealed an average absolute porosity of 30.5% for Murteree shale and 39% for the the Roseneath shale, which is much higher than the results from the MCIP technique and helium porosimetry. This is an indication of having very high isolated porosity and very low permeability. The findings were analysed and validated by the use of SEM images, displaying high amounts of isolated porosity, confirming the high porosity measurement from the pyknometry technique. The results achieved strongly emphasised that gas prone, over-mature, carbonaceous shales have very low effective but very high total porosity. Therefore, it is envisaged that total intergranular porosity holding compressed gas in over-mature source rocks cannot be evaluated using the helium porosimetry and mercury injection techniques. The pyknometry technique supported by the SEM images is an alternative method; however, this method can only measure total, rather than effective, porosity.

scholarly journals The Evaluation and Sensitivity of Decline Curve Modelling

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2765
Author(s):  
Prinisha Manda ◽  
Diakanua Nkazi
Keyword(s):  
Shale Gas ◽  
Goodness Of Fit ◽  
Accuracy Assessment ◽  
Gas Production ◽  
Production Performance ◽  
Logistic Growth ◽  
Gas Reservoirs ◽  
Shale Gas Reservoirs ◽  
Decline Curve ◽  
Exponential Decline

The development of prediction tools for production performance and the lifespan of shale gas reservoirs has been a focus for petroleum engineers. Several decline curve models have been developed and compared with data from shale gas production. To accurately forecast the estimated ultimate recovery for shale gas reservoirs, consistent and accurate decline curve modelling is required. In this paper, the current decline curve models are evaluated using the goodness of fit as a measure of accuracy with field data. The evaluation found that there are advantages in using the current DCA models; however, they also have limitations associated with them that have to be addressed. Based on the accuracy assessment conducted on the different models, it appears that the Stretched Exponential Decline Model (SEDM) and Logistic Growth Model (LGM), followed by the Extended Exponential Decline Model (EEDM), the Power Law Exponential Model (PLE), the Doung’s Model, and lastly, the Arps Hyperbolic Decline Model, provide the best fit with production data.

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