Hydraulic Fracturing Chemical Disclosure Policy and Data Analysis: Metrics and Trends in Transparency

2021 ◽  
Vol 55 (6) ◽  
pp. 3918-3928
Author(s):  
Christopher B. Hill ◽  
Om P. Yadav ◽  
Eakalak Khan
Keyword(s):  
Data Analysis ◽  
Hydraulic Fracturing ◽  
Disclosure Policy

Brittleness evaluation of resource plays by integrating petrophysical and seismic data analysis

2015 ◽  
Vol 3 (2) ◽  
pp. T81-T92 ◽  
Author(s):  
Bo Zhang ◽  
Tao Zhao ◽  
Xiaochun Jin ◽  
Kurt J. Marfurt
Keyword(s):  
Data Analysis ◽  
Hydraulic Fracturing ◽  
Elastic Properties ◽  
Seismic Data ◽  
Mineral Content ◽  
Well Logs ◽  
Support Vector ◽  
Proximal Support Vector Machine ◽  
Classification Pattern ◽  
Laboratory Stress

The main considerations for well planning and hydraulic fracturing in unconventional resources plays include the amount of total organic carbon and how much hydrocarbon can be extracted. Brittleness is the direct measurement of a formation about the ability to create avenues for hydrocarbons when applying hydraulic fracturing. Brittleness can be directly estimated from laboratory stress-strain measurements, rock-elastic properties, and mineral content analysis using petrophysical analysis on well logs. However, the estimated brittleness using these methods only provides “cylinder” estimates near the borehole. We proposed a workflow to estimate brittleness of resource plays in 3D by integrating the petrophysics and seismic data analysis. The workflow began by brittleness evaluation using mineral well logs at the borehole location. Then, we used a proximal support vector machine algorithm to construct a classification pattern between rock-elastic properties and brittleness for the selected benchmark well. The pattern was validated using well-log data that were not used for constructing the classification. Next, we prestack inverted the fidelity preserved seismic gathers to generate a suite of rock-elastic properties volumes. Finally, we obtained a satisfactory brittleness index of target formations by applying the trained classification pattern to the inverted rock-elastic-property volumes.

scholarly journals Persistent Homology: Application To Monitoring Hydraulic Fracturing

2020 ◽  
Vol 23 (6) ◽  
pp. 1192-1212
Author(s):  
Kirill Yurevich Erofeev ◽  
Mansur Tagirovich Ziiatdinov ◽  
Evgenii Vladimirovich Mokshin
Keyword(s):  
Data Analysis ◽  
Hydraulic Fracturing ◽  
Topological Structure ◽  
Prior Information ◽  
Persistent Homology ◽  
Topological Data Analysis ◽  
Analysis Tool ◽  
Data Analysis Tool ◽  
Natural Way ◽  
Topological Data

Persistent homology is a topological data analysis tool which is reflecting changes in topological structure of data along its scale. Application of persistent homology to monitoring hydraulic fracturing which is allowing researchers to consider prior information in a natural way is given in the article

scholarly journals Linkage Investment Opportunity Set (IOS) with Financial Policy in Growing Companies in Indonesia Stock Exchange (BEI)

2018 ◽  
Vol 2 (1) ◽  
pp. 84
Author(s):  
Mrs Marheni
Keyword(s):  
Data Analysis ◽  
Dividend Policy ◽  
Stock Exchange ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Financial Policy ◽  
Funding Policy ◽  
Disclosure Policy ◽  
Funding Policies ◽  
The Difference

The aims of this study were to analyze the influence of disclosure policy, funding policy, dividend policy on IOS and to analyze the difference of IOS influence on disclosure policy, fund policy and dividend policy in the company grow and not grow. The population in this study were companies listed on the Indonesia Stock Exchange there are 509 companies. The sample was chosen by purposive sampling method as many as 88 companies. Methods of data analysis used multiple linear regression analysis and independent t-test. The result of data analysis shows that the company disclosure policy has no effect on IOS. Funding policies as measured by Book Debt Equity companies had a significant effect on IOS. The dividend policy measured by the House of Representatives had no significant effect on IOS. There were IOS differences, disclosure policies, funding policies and dividend policies in the company growing and not growing.

Permeability determination of the medium according to the analysis of laboratory hydraulic fracturing curves.

2021 ◽  
Author(s):  
Helen Novikova ◽  
Mariia Trimonova
Keyword(s):  
Data Analysis ◽  
Hydraulic Fracturing ◽  
Laboratory Experiments ◽  
Similarity Criteria ◽  
Real Field ◽  
Experimental Setup ◽  
Time Period ◽  
Fracture Closure ◽  
Fracturing Process

<p>Recently, attention to the development of low-permeable reservoirs has been increasing. More and more attention is being paid to the search for various methods of data analysis of mini-hydraulic fracturing and computer modeling of the hydraulic fracturing process, which will simplify the entire procedure of hydraulic fracturing in a real field and reduce financial costs. The increase in interest is due to the fact that the results of the hydraulic fracturing are used to determine some important characteristics of the formation.</p><p>One of such important characteristics of a reservoir is permeability. In the course of this study, the data obtained from a series of laboratory experiments on mini-hydraulic fracturing were processed. The main goal was to determine the value of permeability of the medium in which the hydraulic fracture was formed and propagated, with the help of various standard methods. The second objective of the study was to compare the calculated values with real ones known from preliminary conducted laboratory experiments.</p><p>In the frame of the work, the laboratory experiments on mini-hydraulic fracturing were carried out using a special experimental setup [1]. The uniqueness of this experimental setup lies in the fact that it allows to perform a triaxial loading of the sample under consideration. The sample material was selected according to the similarity criteria between the fracturing process in the experiment and the fracturing process in the real field. These features make it possible to approximate the conditions of a laboratory experiment on hydraulic fracturing to real field conditions.</p><p>As a result, pressure-time dependencies were obtained for series of laboratory experiments. Further analysis of the curves was carried out in the time period after fracture closure.</p><p>In the course of data analysis, the flow regimes in the medium during the time period after fracture closure were estimated. After that, the values of permeability were calculated using approach introduced by Nolte [2, 3]. The permeability values were also estimated using the method proposed by Horner [4] and later modified by Nolte [5]. All theoretically obtained values were compared with real values of permeabilities.</p><p><strong>Acknowledgements</strong></p><p>The reported study was funded by RFBR, project number 20-35-80018, and state task 0146-2019-0007.</p><p><strong>References</strong></p><p>1. Trimonova M., Baryshnikov N., Zenchenko E., Zenchenko P., Turuntaev S.: “The Study of the Unstable Fracture Propagation in the Injection Well: Numerical and Laboratory Modelling,” (2017).</p><p>2. Nolte, K. G.: “Determination of Fracture Parameters from Fracturing Pressure Decline,” Las Vegas (1979).</p><p>3. Nolte, K. G.: “A General Analysis of Fracturing Pressure Decline With Application to Three Models,” (1986).</p><p>4. Horner, D. R.: “Pressure Build-Up in Wells,” Netherlands (1951).</p><p>5. Nolte, K. G., Maniere, J. L., Owens, K. A.: “After-Closure Analysis of Fracture Calibration Tests,” Texas (1997).</p>

Sign in / Sign up

Export Citation Format

Share Document