scholarly journals AI/ML assisted shale gas production performance evaluation

2021 ◽  
Author(s):  
Fahad I. Syed ◽  
Temoor Muther ◽  
Amirmasoud K. Dahaghi ◽  
Shahin Negahban
Keyword(s):  
Performance Evaluation ◽  
Shale Gas ◽  
Continuous Process ◽  
The United States ◽  
Gas Production ◽  
Hydrocarbon Exploration ◽  
Production Performance ◽  
Support Vector ◽  
Data Set ◽  
And Performance

AbstractShale gas reservoirs are contributing a major role in overall hydrocarbon production, especially in the United States, and due to the intense development of such reservoirs, it is a must thing to learn the productive methods for modeling production and performance evaluation. Consequently, one of the most adopted techniques these days for the sake of production performance analysis is the utilization of artificial intelligence (AI) and machine learning (ML). Hydrocarbon exploration and production is a continuous process that brings a lot of data from sub-surface as well as from the surface facilities. Availability of such a huge data set that keeps on increasing over time enhances the computational capabilities and performance accuracy through AI and ML applications using a data-driven approach. The ML approach can be utilized through supervised and unsupervised methods in addition to artificial neural networks (ANN). Other ML approaches include random forest (RF), support vector machine (SVM), boosting technique, clustering methods, and artificial network-based architecture, etc. In this paper, a systematic literature review is presented focused on the AI and ML applications for the shale gas production performance evaluation and their modeling.

scholarly journals Assessment of Soft Computing Techniques for the Prediction of Compressive Strength of Bacterial Concrete

Materials ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 489
Author(s):  
Fadi Almohammed ◽  
Parveen Sihag ◽  
Saad Sh. Sammen ◽  
Krzysztof Adam Ostrowski ◽  
Karan Singh ◽  
...  
Keyword(s):  
Compressive Strength ◽  
Performance Evaluation ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Polynomial Kernel ◽  
Support Vector ◽  
Curing Time ◽  
Data Set ◽  
Soft Computing Techniques ◽  
Bacterial Concrete

In this investigation, the potential of M5P, Random Tree (RT), Reduced Error Pruning Tree (REP Tree), Random Forest (RF), and Support Vector Regression (SVR) techniques have been evaluated and compared with the multiple linear regression-based model (MLR) to be used for prediction of the compressive strength of bacterial concrete. For this purpose, 128 experimental observations have been collected. The total data set has been divided into two segments such as training (87 observations) and testing (41 observations). The process of data set separation was arbitrary. Cement, Aggregate, Sand, Water to Cement Ratio, Curing time, Percentage of Bacteria, and type of sand were the input variables, whereas the compressive strength of bacterial concrete has been considered as the final target. Seven performance evaluation indices such as Correlation Coefficient (CC), Coefficient of determination (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Bias, Nash-Sutcliffe Efficiency (NSE), and Scatter Index (SI) have been used to evaluate the performance of the developed models. Outcomes of performance evaluation indices recommend that the Polynomial kernel function based SVR model works better than other developed models with CC values as 0.9919, 0.9901, R2 values as 0.9839, 0.9803, NSE values as 0.9832, 0.9800, and lower values of RMSE are 1.5680, 1.9384, MAE is 0.7854, 1.5155, Bias are 0.2353, 0.1350 and SI are 0.0347, 0.0414 for training and testing stages, respectively. The sensitivity investigation shows that the curing time (T) is the vital input variable affecting the prediction of the compressive strength of bacterial concrete, using this data set.

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.

What fuels oil company risk?

2009 ◽  
Vol 49 (1) ◽  
pp. 183
Author(s):  
Les Coleman
Keyword(s):  
United States ◽  
Oil And Gas ◽  
Research Question ◽  
The United States ◽  
Gas Production ◽  
Risk Propensity ◽  
Oil And Gas Production ◽  
Integrated Theory ◽  
And Performance ◽  
Oil Company

This article has a simple research question: what determines the risks of oil producing companies listed in Australia and the United States, and are there any differences between their risk attitudes? A literature review is used to develop an integrated theory of company risk that is validated using a hand-collected database covering active oil and gas production companies in Australia and the United States. Risk in both countries proved to be a function of company risk propensity and risk management, which each had a small number of deep-seated drivers spread across company structure, governance and performance. These common risk-related features between companies in geographically remote countries point to the complexity of achieving portfolio diversification.

State Support and Assessment of the Feasibility of Shale Gas Production

2021 ◽  
pp. 225-236
Author(s):  
Mikhail I. Khoroshiltsev
Keyword(s):  
United States ◽  
Hydraulic Fracturing ◽  
Economic Efficiency ◽  
Shale Gas ◽  
The United States ◽  
Industrial Sector ◽  
Gas Production ◽  
Technological Breakthrough ◽  
Tight Reservoirs ◽  
Hydrocarbon Deposits

The article analyzes shale gas production in the United States and calculates its economic efficiency. The development of shale gas production became possible due to the combination of tight reservoirs in a single technological process of drilling and hydraulic fracturing. A technological breakthrough in gas production made it economically attractive for investors (considering the prices of that period) to develop unconventional hydrocarbon deposits. At the same time, like any new industrial sector, the development of shale gas is associated with significant costs at various levels.

scholarly journals The concept of well integrity in gas production activities

2016 ◽  
Vol 23 (2) ◽  
pp. 205-213 ◽  
Author(s):  
Peter Reichetseder
Keyword(s):  
Drinking Water ◽  
Shale Gas ◽  
Environmental Protection Agency ◽  
Marcellus Shale ◽  
The United States ◽  
Gas Production ◽  
Well Integrity ◽  
Drinking Water Resources ◽  
The Us ◽  
Geological Situation

Abstract Shale gas production in the US, predominantly from the Marcellus shale, has been accused of methane emissions and contaminating drinking water under the suspicion that this is caused by hydraulic fracturing in combination with leaking wells. Misunderstandings of the risks of shale gas production are widespread and are causing communication problems. This paper discusses recent preliminary results from the US Environmental Protection Agency (EPA) draft study, which is revealing fact-based issues: EPA did not find evidence that these mechanisms have led to widespread, systemic impacts on drinking water resources in the United States, which contrasts many broad-brushed statements in media and public. The complex geological situation and extraction history of oil, gas and water in the Marcellus area in Pennsylvania is a good case for learnings and demonstrating the need for proper analysis and taking the right actions to avoid problems. State-of-the-art technology and regulations of proper well integrity are available, and their application will provide a sound basis for shale gas extraction.

Bottlenecks and Countermeasures in Shale Gas Exploration and Development of China

2014 ◽  
Vol 978 ◽  
pp. 157-160
Author(s):  
Rong Huo ◽  
Kai Bo Duan
Keyword(s):  
United States ◽  
Economic Growth ◽  
Natural Gas ◽  
Shale Gas ◽  
Emerging Technologies ◽  
The United States ◽  
Gas Production ◽  
Oil Exploration ◽  
The World ◽  
Exploration And Development

With the furthering of China’s all round reform, there will be greater economic growth and more urgent demands for energy. And the achievements of shale gas exploration and development in the United States provide a lot of lessons for domestic gas and oil exploration and development [Figure. 1]. However, the introduction of the matured foreign exploration and development technologies also suffers a great challenge. This paper aims to analyzing the problems in the exploration and development in China’s typical exploration areas and the measures that have been taken. Also, it sums up the emerging technologies and methods in the world, hoping to boost the future exploration and development of shale gas in China in a certain way. Fig. 1 U.S. dry natural gas production ( drawn from EIA)

The Firm Value and Marketing Intensity Decision in Conditions of Financial Constraint: A Comparative Study of the United States and Latin America

2020 ◽  
Vol 28 (3) ◽  
pp. 21-39
Author(s):  
Walter Palomino-Tamayo ◽  
Juan Timana ◽  
Julio Cerviño
Keyword(s):  
United States ◽  
Latin America ◽  
Latin American ◽  
Firm Value ◽  
Financial Constraints ◽  
The United States ◽  
Financial Constraint ◽  
Data Set ◽  
And Performance ◽  
Marketing Intensity

Marketing managers generally have to make marketing decisions under financial constraints (i.e., the firm’s inability to generate cash flow for investments and marketing), with limited assurance of the outcomes. Little investigation has been made into the effect of financial constraints on marketing intensity and the subsequent effect on firm value and performance, particularly when it is a volatile environment (e.g., Latin America) that creates the financial constraints. Using a conceptual framework grounded in agency theory, the authors develop a model and test it using a panel data set from the United States and five Latin American countries. The results indicate that financial constraints have a negative effect on marketing intensity and ultimately negatively affect firm value and performance. Furthermore, this study confirms the effect of three moderators—market sensitivity, country governance quality, and country economic development distance—on the relationship between financial constraint and marketing intensity and helps explain differences across the United States and Latin America.

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