Production Forecasting for Shale Gas Reservoir Wells using a Simulator that Honors the Microstructure of Shale Gas Reservoirs and the Physics of Fluids In Nano-Porous Media

2013 ◽  
Author(s):  
G. Michel ◽  
F. Civan ◽  
R. Sigal ◽  
D. Devegowda
Keyword(s):  
Porous Media ◽  
Shale Gas ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Shale Gas Reservoir ◽  
Production Forecasting ◽  
Shale Gas Reservoirs

scholarly journals A Workflow for Integrated Geological Modeling for Shale Gas Reservoirs: A Case Study of the Fuling Shale Gas Reservoir in the Sichuan Basin, China

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Xiaofei Shang ◽  
Huawei Zhao ◽  
Shengxiang Long ◽  
Taizhong Duan
Keyword(s):  
Shale Gas ◽  
Production Optimization ◽  
Natural Fracture ◽  
Geological Modeling ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Shale Gas Reservoir ◽  
Shale Gas Reservoirs ◽  
Stratigraphic Model

Shale gas reservoir evaluation and production optimization both require geological models. However, currently, shale gas modeling remains relatively conventional and does not reflect the unique characteristics of shale gas reservoirs. Based on a case study of the Fuling shale gas reservoir in China, an integrated geological modeling workflow for shale gas reservoirs is proposed to facilitate its popularization and application and well improved quality and comparability. This workflow involves four types of models: a structure-stratigraphic model, reservoir (matrix) parameter model, natural fracture (NF) model, and hydraulic fracture (HF) model. The modeling strategies used for the four types of models vary due to the uniqueness of shale gas reservoirs. A horizontal-well lithofacies sublayer calibration-based method is employed to build the structure-stratigraphic model. The key to building the reservoir parameter model lies in the joint characterization of shale gas “sweet spots.” The NF models are built at various scales using various methods. Based on the NF models, the HF models are built by extended simulation and microseismic inversion. In the entire workflow, various types of models are built in a certain sequence and mutually constrain one another. In addition, the workflow contains and effectively integrates multisource data. Moreover, the workflow involves multiple model integration processes, which is the key to model quality. The selection and optimization of modeling methods, the innovation and development of modeling algorithms, and the evaluation techniques for model uncertainty are areas where breakthroughs may be possible in the geological modeling of shale gas reservoirs. The workflow allows the complex process of geological modeling of shale gas reservoirs to be more systematic. It is of great significance for a dynamic analysis of reservoir development, from individual wells to the entire gas field, and for optimizing both development schemes and production systems.

scholarly journals Simulation Study to Evaluate the Impact of Fracture Parameters on Shale Gas Productivity

2020 ◽  
Vol 39 (2) ◽  
pp. 432-442
Author(s):  
Abdul Majeed Shar ◽  
Waheed Ali Abro ◽  
Aftab Ahmed Mahesar ◽  
Kun Sang Lee
Keyword(s):  
Shale Gas ◽  
Gas Production ◽  
Simulation Software ◽  
Production Performance ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Shale Gas Reservoir ◽  
Fracture Parameters ◽  
Shale Gas Reservoirs ◽  
The Impact

The production from shale gas reservoirs has significantly increased due to technological advancements. The shale gas reservoirs are very heterogeneous and the heterogeneity has a significant effect on the quality and productivity of reservoirs. Hence, it is essential to study the behavior of such reservoirs for accurate modelling and performance prediction. To evaluate the impact of fracture parameters on shale gas reservoir productivity using CMG (Computer Modelling Group) stars simulation software was the main objective of this study. In this paper, a comprehensive analysis considering an example shale gas reservoir was conducted for production performance analysis considering uniform and non-uniform fractures configurations. Several simulations were performed by considering the multi-stage hydraulically fractured reservoir. The sensitivities conducted includes the different cases of moderate and severe heterogeneity along with variable fractures half-length, effect of changing fracture spacing, variable fracture conductivities. The simulation results showed that by increasing conductivity of fracture increases the gas production rate significantly. Moreover, cases of reservoir permeability heterogeneity were analyzed which show the significant effect on gas rate and on cumulative gas production. The results of this study can be used to improve the effectiveness in designing and developing of shale gas reservoirs and also to improve the accuracy of analyzing heterogeneous shale gas reservoir performance.

scholarly journals An Identified Method for Lacustrine Shale Gas Reservoir Lithofacies Using Logs: A Case Study for No. 7 Section in Yanchang Formation in Ordos Basin

2015 ◽  
Vol 8 (1) ◽  
pp. 297-307
Author(s):  
Hongyan Yu ◽  
Zhenliang Wang ◽  
Hao Cheng ◽  
Qianqian Yin ◽  
Bojiang Fan ◽  
...  
Keyword(s):  
Decision Tree ◽  
Mineral Composition ◽  
Shale Gas ◽  
Ordos Basin ◽  
Multidimensional Data ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Yanchang Formation ◽  
Shale Gas Reservoir ◽  
Shale Gas Reservoirs

Unconventional reservoirs are keys to oil and gas exploration and development, especially shale gas reservoirs. Discriminated shale gas reservoir lithofacies are, in particular, a primary problem in shale gas reservoir engineering. The mineral composition will affect both absorbed and free gas contents, therefore their identification is important. The mineral composition is one part of lithofacies. The shale content has always been used in previous lithological identifications: this method is effective in sand reservoirs; however, it is not suitable for use in shale gas reservoirs. This paper takes No.7 section in Yanchang formation in Ordos basin as an example. Through a lithological analysis, it was concluded that overlap method and cross-plot method are not also inappropriate for shale gas reservoirs. The Ordos basin shale gas reservoir is divided into seven lithofacies. We form a mathematical method and apply it to shale gas reservoirs using the shale volume and ΔlgR which are available from conventional well logging and reflect organic matter in the processed dataset. Decision tree is used here. However, there were too many parameters to discriminate all lithofacies precisely. Principal component analysis (PCA) is a technique used to reduce multidimensional data sets to lower dimensions for analysis. This technique can be useful in petro-physics and geology as a preliminary method of combining multiple logs into a single entity or two logs without losing information. Combining PCA and a decision tree algorithm, the lithofacies of a shale gas reservoir were accurately discriminated.

scholarly journals A Novel Optimization Workflow Coupling Statistics-Based Methods to Determine Optimal Well Spacing and Economics in Shale Gas Reservoir with Complex Natural Fractures

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3965
Author(s):  
Cheng Chang ◽  
Chuxi Liu ◽  
Yongming Li ◽  
Xiaoping Li ◽  
Wei Yu ◽  
...  
Keyword(s):  
Shale Gas ◽  
History Matching ◽  
Net Present Value ◽  
Hydraulic Fractures ◽  
Natural Fractures ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Shale Gas Reservoir ◽  
Shale Gas Reservoirs ◽  
Well Spacing

In order to account for big uncertainties such as well interferences, hydraulic and natural fractures’ properties and matrix properties in shale gas reservoirs, it is paramount to develop a robust and efficient approach for well spacing optimization. In this study, a novel well spacing optimization workflow is proposed and applied to a real shale gas reservoir with two-phase flow, incorporating the systematic analysis of uncertainty reservoir and fracture parameters. One hundred combinations of these uncertainties, considering their interactions, were gathered from assisted history matching solutions, which were calibrated by the actual field production history from the well in the Sichuan Basin. These combinations were used as direct input to the well spacing optimization workflow, and five “wells per section” spacing scenarios were considered, with spacing ranging from 157 m (517 ft) to 472 m (1550 ft). An embedded discrete fracture model was used to efficiently model both hydraulic fractures and complex natural fractures non-intrusively, along with a commercial compositional reservoir simulator. Economic analysis after production simulation was then carried out, by collecting cumulative gas and water production after 20 years. The net present value (NPV) distributions of the different well spacing scenarios were calculated and presented as box-plots with a NPV ranging from 15 to 35 million dollars. It was found that the well spacing that maximizes the project NPV for this study is 236 m (775 ft), with the project NPV ranging from 15 to 35 million dollars and a 50th percentile (P50) value of 25.9 million dollars. In addition, spacings of 189 m (620 ft) and 315 m (1033 ft) can also produce substantial project profits, but are relatively less satisfactory than the 236 m (775 ft) case when comparing the P25, P50 and P75 values. The results obtained from this study provide key insights into the field pilot design of well spacing in shale gas reservoirs with complex natural fractures.

scholarly journals Analysis of the Influence of Different Fracture Network Structures on the Production of Shale Gas Reservoirs

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Ming Yue ◽  
Xiaohe Huang ◽  
Fanmin He ◽  
Lianzhi Yang ◽  
Weiyao Zhu ◽  
...  
Keyword(s):  
Finite Element ◽  
Shale Gas ◽  
Flow Direction ◽  
Fracture Network ◽  
Gas Production ◽  
Low Flow ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Shale Gas Reservoir ◽  
Gas Seepage

Volume fracturing is a key technology in developing unconventional gas reservoirs that contain nano/micron pores. Different fracture structures exert significantly different effects on shale gas production, and a fracture structure can be learned only in a later part of detection. On the basis of a multiscale gas seepage model considering diffusion, slippage, and desorption effects, a three-dimensional finite element algorithm is developed. Two finite element models for different fracture structures for a shale gas reservoir in the Sichuan Basin are established and studied under the condition of equal fracture volumes. One is a tree-like fracture, and the other is a lattice-like fracture. Their effects on the production of a fracture network structure are studied. Numerical results show that under the same condition of equal volumes, the production of the tree-like fracture is higher than that of the lattice-like fracture in the early development period because the angle between fracture branches and the flow direction plays an important role in the seepage of shale gas. In the middle and later periods, owing to a low flow rate, the production of the two structures is nearly similar. Finally, the lattice-like fracture model is regarded as an example to analyze the factors of shale properties that influence shale gas production. The analysis shows that gas production increases along with the diffusion coefficient and matrix permeability. The increase in permeability leads to a larger increase in production, but the decrease in permeability leads to a smaller decrease in production, indicating that the contribution of shale gas production is mainly fracture. The findings of this study can help better understand the influence of different shapes of fractures on the production in a shale gas reservoir.

A New Probabilistic Approach for Uncertainty Quantification in Well Performance of Shale Gas Reservoirs

SPE Journal ◽  
2016 ◽  
Vol 21 (06) ◽  
pp. 2038-2048 ◽  
Author(s):  
Wei Yu ◽  
Xiaosi Tan ◽  
Lihua Zuo ◽  
Jenn-Tai Liang ◽  
Hwa C. Liang ◽  
...  
Keyword(s):  
Uncertainty Quantification ◽  
Shale Gas ◽  
Probabilistic Approach ◽  
Model Parameters ◽  
Well Performance ◽  
Gas Reservoirs ◽  
Production Forecasting ◽  
Shale Gas Reservoirs ◽  
Decline Curve ◽  
Curve Model

Summary Over the past decade, technological advancements in horizontal drilling and multistage fracturing enable natural gas to be economically produced from tight shale formations. However, because of limited availability of the production data as well as the complex gas-transport mechanisms and fracture geometries, there still exist great uncertainties in production forecasting and reserves estimation for shale gas reservoirs. The rapid pace of shale gas development makes it important to develop a new and efficient probabilistic-based methodology for history matching, production forecasting, reserves estimates, and uncertainty quantification that are critical for the decision-making processes. In this study, we present a new probabilistic approach with the Bayesian methodology combined with Markov-chain Monte Carlo (MCMC) sampling and a fractional decline-curve (FDC) model to improve the efficiency and reliability of the uncertainty quantification in well-performance forecasting for shale gas reservoirs. The FDC model not only can effectively capture the long-tail phenomenon of shale gas-production decline curves but also can obtain a narrower range of production prediction than the classical Arps model. To predict the posterior distributions of the decline-curve model parameters, we use a more-efficient adaptive Metropolis (AM) algorithm in place of the standard Metropolis-Hasting (MH) algorithm. The AM algorithm can form the Markov chain of decline-curve model parameters efficiently by incorporating the correlation between the model parameters. With the predicted posterior distributions of the FDC model parameters generated by the AM algorithm, the uncertainty in production forecasts and estimated-ultimate-recovery (EUR) prediction can then be quantified. This work provides an efficient and robust tool that is based on a new probabilistic approach for production forecasting, reserves estimations, and uncertainty quantification for shale gas reservoirs.

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