Numerical Simulation of Gas Production From Tight, Ultratight and Shale Gas Reservoirs: Flow Regimes and Geomechanical Effects

2015 ◽  
Author(s):  
Rasoul Nazari Moghaddam ◽  
Shokoufeh Aghabozorgi ◽  
Jalal Foroozesh
Keyword(s):  
Numerical Simulation ◽  
Shale Gas ◽  
Flow Regimes ◽  
Gas Production ◽  
Gas Reservoirs ◽  
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.

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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