scholarly journals A mathematical model for estimating effective stimulated reservoir volume

2021 ◽  
Author(s):  
Adamu Umar Ibrahim ◽  
Berihun Mamo Negash ◽  
Md. Tauhidur Rahman ◽  
Akilu Suleiman ◽  
Danso David Kwaku
Keyword(s):  
Shale Gas ◽  
Current Model ◽  
Fractured Reservoirs ◽  
Model Development ◽  
Fractured Reservoir ◽  
Gas Reservoirs ◽  
Stimulated Reservoir Volume ◽  
Reservoir Volume ◽  
Shale Gas Reservoirs ◽  
Multi Stage

AbstractThis study presents a model application for the evaluation of Effective Stimulated Reservoir Volume (ESRV) in shale gas reservoirs. This current model is faster, cheaper, and readily available for estimating ESRV compared to previously published models. Key controlling parameters for efficient ESRV modeling, including geomechanical parameters and time, are considered for the model development. The model was validated for both single and multi-stage fractured reservoirs. For the single fractured reservoir, an ESRV of 3.07 × 106 ft3 was estimated against 3.99 × 106 ft3 of ESRV-FEM field data. Whereas, 7.00 × 109 ft3 ESRV was estimated from the multi-stage fractured reservoir against 7.90 × 109 ft3 of fractal-based model results. Stress dependence, time dependence, and permeability dependence of shale gas reservoirs are found to be essential parameters for the successful calculation of ESRV in reservoirs. An ESRV determined using this method can obtain the estimated ultimate recovery, propped volume, optimal fracture length, and spacing in fractured shale gas reservoirs.

scholarly journals APPLICATION OF FRACTAL GEOMETRY IN EVALUATION OF EFFECTIVE STIMULATED RESERVOIR VOLUME IN SHALE GAS RESERVOIRS

Fractals ◽  
2017 ◽  
Vol 25 (04) ◽  
pp. 1740007 ◽  
Author(s):  
GUANGLONG SHENG ◽  
YULIANG SU ◽  
WENDONG WANG ◽  
FARZAM JAVADPOUR ◽  
MEIRONG TANG
Keyword(s):  
Hydraulic Fracturing ◽  
Shale Gas ◽  
Fractal Geometry ◽  
Fracture Network ◽  
Gas Reservoirs ◽  
Stimulated Reservoir Volume ◽  
Reservoir Volume ◽  
Adsorbed Gas ◽  
Shale Gas Reservoirs ◽  
Shale Reservoirs

According to hydraulic-fracturing practices conducted in shale reservoirs, effective stimulated reservoir volume (ESRV) significantly affects the production of hydraulic fractured well. Therefore, estimating ESRV is an important prerequisite for confirming the success of hydraulic fracturing and predicting the production of hydraulic fracturing wells in shale reservoirs. However, ESRV calculation remains a longstanding challenge in hydraulic-fracturing operation. In considering fractal characteristics of the fracture network in stimulated reservoir volume (SRV), this paper introduces a fractal random-fracture-network algorithm for converting the microseismic data into fractal geometry. Five key parameters, including bifurcation direction, generating length ([Formula: see text]), deviation angle ([Formula: see text]), iteration times ([Formula: see text]) and generating rules, are proposed to quantitatively characterize fracture geometry. Furthermore, we introduce an orthogonal-fractures coupled dual-porosity-media representation elementary volume (REV) flow model to predict the volumetric flux of gas in shale reservoirs. On the basis of the migration of adsorbed gas in porous kerogen of REV with different fracture spaces, an ESRV criterion for shale reservoirs with SRV is proposed. Eventually, combining the ESRV criterion and fractal characteristic of a fracture network, we propose a new approach for evaluating ESRV in shale reservoirs. The approach has been used in the Eagle Ford shale gas reservoir, and results show that the fracture space has a measurable influence on migration of adsorbed gas. The fracture network can contribute to enhancement of the absorbed gas recovery ratio when the fracture space is less than 0.2 m. ESRV is evaluated in this paper, and results indicate that the ESRV accounts for 27.87% of the total SRV in shale gas reservoirs. This work is important and timely for evaluating fracturing effect and predicting production of hydraulic fracturing wells in shale reservoirs.

scholarly journals Productivity Model for Shale Gas Reservoir with Comprehensive Consideration of Multi-mechanisms

2015 ◽  
Vol 8 (1) ◽  
pp. 235-247 ◽  
Author(s):  
Ya Deng ◽  
Rui Guo ◽  
Zhongyuan Tian ◽  
Cong Xiao ◽  
Haiying Han ◽  
...  
Keyword(s):  
Shale Gas ◽  
Horizontal Well ◽  
Flow Behavior ◽  
Stress Sensitivity ◽  
Transitional Flow ◽  
Gas Reservoirs ◽  
Type Curves ◽  
Stimulated Reservoir Volume ◽  
Reservoir Volume ◽  
Shale Gas Reservoirs

Multi-stage fracturing horizontal well currently has been proved to be the most effective method to produce shale gas. This method can activate the natural fractures system defined as stimulated reservoir volume (SRV), the remaining region similarly is defined as un-stimulated reservoir volume (USRV). At present, no type curves have been developed for hydraulic fractured shale gas reservoirs in which the SRV zone has triple-porosity dual-depletion flow behavior and the USRV zone has double porosity flow behavior. In this paper, the SRV zone and USRV zone respectively are simplified as cubic triple-porosity and slab dual porosity media. We have established a new productivity model for multifractured horizontal well shale gas with Comprehensive consideration of desorption, diffusion, viscous flow, stress sensitivity and dual-depletion mechanism in matrix. The rate transient responses are inverted into real time space with stehfest numerical inversion algorithm. Type curves are plotted, and different flow regimes in shale gas reservoirs are identified. Effects of relevant parameters are analyzed as well. The whole flow period can be divided into 8 regimes: bilinear flow in SRV; pseudo elliptic flow; dual inter-porosity flow; transitional flow; linear flow in USRV; inter-porosity flow and boundary-dominated flow. The stress sensitivity basically has negative influence on the whole productivity period .The less the value of Langmuir volume and the lager the value of Langmuir pressure, the more lately the inter-porosity flow and boundary-dominated flow occurs. It in concluded that the USRV zone has positive influence on production and could not be ignored.

scholarly journals A Comprehensive Model for Estimating Stimulated Reservoir Volume Based on Flowback Data in Shale Gas Reservoirs

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Qi Chen ◽  
Shaojun Wang ◽  
Dan Zhu ◽  
Guoxuan Ren ◽  
Yuan Zhang ◽  
...  
Keyword(s):  
Relative Permeability ◽  
Shale Gas ◽  
Stress Sensitivity ◽  
Comprehensive Model ◽  
Gas Reservoirs ◽  
Horizontal Drilling ◽  
Stimulated Reservoir Volume ◽  
Reservoir Volume ◽  
Microseismic Data ◽  
Shale Gas Reservoirs

Stimulated reservoir volume (SRV) which is generated by horizontal drilling with multistage hydraulic fracturing governs the production in the shale gas reservoirs. Although microseismic data has been used to estimate the SRV, it is high-priced and sometimes overestimated. Additionally, the effect of stress sensitivity on SRV is not considered in abnormal overpressure areas. Thus, the objective of this work is to characterize subsurface fracture networks with stress sensitivity of permeability through the shale gas well production data of the early flowback stage. The flowback regions are first identified with the flowback data of two shale gas wells in South China. Then, we measured the permeability stress sensitivity of the core after fracturing, coupled to the dynamic relative permeability (DRP) calculation to obtain an accurate and simple DRP curve. After that, a comprehensive model is built considering dynamic two-phase relative permeability function and stress sensitivity. Finally, we compared the calculated results with the microseismic data. The results show that the proposed model could reasonably predict the SRV using the flowback data after fracturing. Additionally, compared with the microseismic data, the stress sensitivity should be included, especially in the abnormal overpressure block. It is believed that this mathematical model is accurate and useful. The work provides an efficient approach to estimate stimulated reservoir volume in the shale gas reservoirs.

History Matching of Stimulated Reservoir Volume of Shale-Gas Reservoirs Using an Iterative Ensemble Smoother

SPE Journal ◽  
2017 ◽  
Vol 23 (02) ◽  
pp. 346-366 ◽  
Author(s):  
Haibin Chang ◽  
Dongxiao Zhang
Keyword(s):  
Hydraulic Fracturing ◽  
Shale Gas ◽  
History Matching ◽  
Fracture Network ◽  
Hydraulic Fractures ◽  
Gas Reservoirs ◽  
Stimulated Reservoir Volume ◽  
Reservoir Volume ◽  
Shale Gas Reservoirs ◽  
Iterative Ensemble Smoother

Summary Economic production from shale-gas reservoirs typically relies on the drilling of horizontal wells and hydraulic fracturing in multiple stages. In addition to the creation of hydraulic fractures, hydraulic-fracturing treatment can also reopen existing natural fractures, which can create a complex-fracture network. The area that is covered by the fracture network is usually termed the stimulated reservoir volume (SRV), and the spatial extent and properties of the SRV are crucial for shale-gas-production behavior. In this work, we propose a method for history matching of the SRV of shale-gas reservoirs using production data. For each hydraulic-fracturing stage, the fracture network is parameterized with one major fracture of the hydraulic fractures and the SRV that represents minor hydraulic fractures and reopened natural fractures. The major fracture is modeled explicitly, whereas the SRV is modeled by the dual-permeability/dual-porosity (DP/DP) model. Moreover, the spatial extent of the SRV is parameterized by the level-set-function values on a predefined representing-node system. After parameterization, an iterative ensemble smoother is used to perform history matching. Both single-stage-fracturing cases and multistage-fracturing cases are set up to test the performance of the proposed method. Numerical results demonstrate that by use of the proposed method, the SRV can be well-recognized by assimilating production data.

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