Understanding and Predicting Fayetteville Shale Gas Production Through Integrated Seismic-to-Simulation Reservoir Characterization Workflow

2011 ◽  
Author(s):  
Hariharan Ramakrishnan ◽  
Eva A. Peza ◽  
Shekhar Sinha ◽  
Miriam A. Woods ◽  
Chris Ikeocha ◽  
...  
Keyword(s):  
Shale Gas ◽  
Reservoir Characterization ◽  
Gas Production ◽  
Fayetteville Shale

scholarly journals New Hybrid Approach for Developing Automated Machine Learning Workflows: A Real Case Application in Evaluation of Marcellus Shale Gas Production

Fuels ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 286-303
Author(s):  
Vuong Van Pham ◽  
Ebrahim Fathi ◽  
Fatemeh Belyadi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Shale Gas ◽  
Field Data ◽  
Marcellus Shale ◽  
Hybrid Approach ◽  
Gas Production ◽  
Bayesian Optimization ◽  
Real Field ◽  
Engineering Problems

The success of machine learning (ML) techniques implemented in different industries heavily rely on operator expertise and domain knowledge, which is used in manually choosing an algorithm and setting up the specific algorithm parameters for a problem. Due to the manual nature of model selection and parameter tuning, it is impossible to quantify or evaluate the quality of this manual process, which in turn limits the ability to perform comparison studies between different algorithms. In this study, we propose a new hybrid approach for developing machine learning workflows to help automated algorithm selection and hyperparameter optimization. The proposed approach provides a robust, reproducible, and unbiased workflow that can be quantified and validated using different scoring metrics. We have used the most common workflows implemented in the application of artificial intelligence (AI) and ML in engineering problems including grid/random search, Bayesian search and optimization, genetic programming, and compared that with our new hybrid approach that includes the integration of Tree-based Pipeline Optimization Tool (TPOT) and Bayesian optimization. The performance of each workflow is quantified using different scoring metrics such as Pearson correlation (i.e., R2 correlation) and Mean Square Error (i.e., MSE). For this purpose, actual field data obtained from 1567 gas wells in Marcellus Shale, with 121 features from reservoir, drilling, completion, stimulation, and operation is tested using different proposed workflows. A proposed new hybrid workflow is then used to evaluate the type well used for evaluation of Marcellus shale gas production. In conclusion, our automated hybrid approach showed significant improvement in comparison to other proposed workflows using both scoring matrices. The new hybrid approach provides a practical tool that supports the automated model and hyperparameter selection, which is tested using real field data that can be implemented in solving different engineering problems using artificial intelligence and machine learning. The new hybrid model is tested in a real field and compared with conventional type wells developed by field engineers. It is found that the type well of the field is very close to P50 predictions of the field, which shows great success in the completion design of the field performed by field engineers. It also shows that the field average production could have been improved by 8% if shorter cluster spacing and higher proppant loading per cluster were used during the frac jobs.

Digital Workflow to Enhance Reservoir Management Strategies for A Complex Oil Field Through Real Time and Advanced Engineering Monitoring Solution

2021 ◽  
Author(s):  
Julieta Alvarez ◽  
Oswaldo Espinola ◽  
Luis Rodrigo Diaz ◽  
Lilith Cruces
Keyword(s):  
Real Time ◽  
Reservoir Characterization ◽  
Management Strategies ◽  
Reservoir Management ◽  
Gas Production ◽  
Oil Field ◽  
Oil Reservoirs ◽  
Production Operation ◽  
Digital Workflow ◽  
Operational Decisions

Abstract Increase recovery from mature oil reservoirs requires the definition of enhanced reservoir management strategies, involving the implementation of advanced methodologies and technologies in the field's operation. This paper presents a digital workflow enabling the integration of commonly isolated elements such as: gauges, flowmeters, inflow control devices; analysis methods and data, used to improve scientific understanding of subsurface flow dynamics and determine improved operational decisions that support field's reservoir management strategy. It also supports evaluation of reservoir extent, hydraulic communication, artificial lift impact in the near-wellbore zone and reservoir response to injected fluids and coning phenomenon. This latest is used as an example to demonstrate the applicability of this workflow to improve and support operational decisions, minimizing water and gas production due to coning, that usually results in increasing production operation costs and it has a direct impact decreasing reservoir energy in mature saturated oil reservoirs. This innovative workflow consists on the continuous interpretation of data from downhole gauges, referred in this paper as data-driven; as well as analytical and numerical simulation methodologies using real-time raw data as an input, referred in this paper as model-driven, not commonly used to analyze near wellbore subsurface phenomena like coning and its impact in surface operation. The resulting analyses are displayed through an extensive visualization tool that provides instant insight to reservoir characterization and productivity groups, improving well and reservoir performance prediction capabilities for complex reservoirs such as mature saturated reservoirs with an associated aquifer, where undesired water and gas production is a continuous challenge that incorporates unexpected operational expenses.

Lithology and sedimentary heterogeneity of the Longmaxi Shale in the southern Sichuan Basin, China

2021 ◽  
pp. 1-49
Author(s):  
Boling Pu ◽  
Dazhong Dong ◽  
Ning Xin-jun ◽  
Shufang Wang ◽  
Yuman Wang ◽  
...  
Keyword(s):  
Continental Shelf ◽  
Deep Water ◽  
Shale Gas ◽  
Sichuan Basin ◽  
Sedimentary Environment ◽  
Gas Production ◽  
Carbonaceous Shale ◽  
Gas Wells ◽  
Longmaxi Shale ◽  
Siliceous Shale

Producers have always been eager to know the reasons for the difference in the production of different shale gas wells. The Southern Sichuan Basin in China is one of the main production zones of Longmaxi shale gas, while the shale gas production is quite different in different shale gas wells. The Longmaxi formation was deposited in a deep water shelf that had poor circulation with the open ocean, and is composed of a variety of facies that are dominated by fine-grained (clay- to silt-size) particles with a varied organic matter distribution, causing heterogeneity of the shale gas concentration. According to the different mother debris and sedimentary environment, we recognized three general sedimentary subfacies and seven lithofacies on the basis of mineralogy, sedimentary texture and structures, biota and the logging response: (1) there are graptolite-rich shale facies, siliceous shale facies, calcareous shale facies, and a small amount of argillaceous limestone facies in the deep - water shelf in the Weiyuan area and graptolite-rich shale facies and carbonaceous shale facies in the Changning area; (2) there are argillaceous shale facies and argillaceous limestone facies in the semi - deep - water continental shelf of the Weiyuan area and silty shale facies in the Changning area; (3) argillaceous shale facies are mainly developed in the shallow muddy continental shelf in the Weiyuan area, while silty shale facies mainly developed in the shallow shelf in the Changning area. Judging from the biostratigraphy of graptolite, the sedimentary environment was different in different stages.

Sliding behavior of silica ball-shale rock contact under polyacrylamide aqueous solutions

2021 ◽  
pp. 1-25
Author(s):  
Huijie Zhang ◽  
Shuhai Liu
Keyword(s):  
Adverse Effect ◽  
Shale Gas ◽  
Normal Load ◽  
Gas Production ◽  
Wear Depth ◽  
Brine Solution ◽  
Shale Rock ◽  
Different Types ◽  
The Coefficient Of Friction ◽  
Specific Speed

Abstract The tribological properties of proppant particle sliding on shale rock determine the shale gas production. This work focuses on investigating the impacts of sliding speed on the coefficient of friction (COF) and wear of the silica ball-shale rock contact, which was lubricated by water or different types of polyacrylamide (PAM) aqueous or brine solution. The experimental results show that both boundary and mixed lubrication occur under specific speed and normal load. COF and wear depth of shale rock under water are higher than those under PAM solution due to superior lubrication of PAM. COF of shale rock under PAM brine solution increases and the wear of the rock is more serious, attributed to the corrosion of shale rock and adverse effect on lubrication of PAM by brine.

New insights from shale gas production at the microscopic scale

2018 ◽  
Vol 41 (11) ◽  
Author(s):  
Natalia Kovalchuk ◽  
Constantinos Hadjistassou
Keyword(s):  
Shale Gas ◽  
Gas Production ◽  
Microscopic Scale
Sign in / Sign up

Export Citation Format

Share Document