scholarly journals Risk Decision-Making Technology in Gas Reservoir Development at Sichuan Basin

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Guo Yu ◽  
Haitao Li ◽  
Yanru Chen ◽  
Linqing Liu ◽  
Dongming Zhang
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Stochastic Simulation ◽  
Development Planning ◽  
Gas Reservoir ◽  
Probability Curve ◽  
Scanning Method ◽  
Reservoir Development ◽  
Risk Grade ◽  
Risk Decision

During the development of complex gas reservoirs, the risk decision-making problem often emerges. Thus, the study on risk assessment is an important tool used to identify potential hazards and create appropriate avoidance measures accordingly. Based on the analysis of seven types of risk factors in gas reservoir development planning, this paper aims to clarify the logical relationship between the risk factors in the strategic planning of natural gas development. The comprehensive research on target risks in the gas reservoir development planning based on stochastic simulation was carried out. The “probability curve scanning method” was used to evaluate objective risk factors, while the decision-making risk factors were evaluated using the “probability curve displacement method.” According to the realization probability and dispersion degree of the planned target combined with the risk grade evaluation matrix, the planning target evaluation risk grade was implemented. Moreover, the planning unit risk grade evaluation was obtained at different stages. Regarding the specific production capacity conditions in gas wells (horizontal and vertical wells) and gas reservoir water invasion, the probability method with Monte Carlo stochastic simulation was used to calculate the production and water invasion volumes. The established decision-making risk technology for gas reservoir development, along with the associated supporting procedures, can be used to evaluate the risks of reservoir development planning, production, and water invasion.

scholarly journals Risk Decision-making Technology in Gas Reservoir Development at Sichuan Basin

2021 ◽  
Author(s):  
Guo Yu ◽  
Haitao Li ◽  
Yanru Chen ◽  
Linqing Liu ◽  
Zhang Dongming
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Stochastic Simulation ◽  
Development Planning ◽  
Gas Reservoir ◽  
Probability Curve ◽  
Scanning Method ◽  
Reservoir Development ◽  
Risk Grade ◽  
Risk Decision

Abstract During the development of complex gas reservoirs, the risk decision-making problem often emerges. Thus, the study on risk assessment is an important tool used to identify potential hazards and create appropriate avoidance measures accordingly. Based on the analysis of seven types of risk factors in gas reservoir development planning, this paper aims to clarify the logical relationship between the risk factors in the strategic planning of natural gas development. The comprehensive research on target risks in the gas reservoir development planning based on stochastic simulation was carried out. The “probability curve scanning method” was used to evaluate objective risk factors, while the decision-making risk factors were evaluated using the “probability curve displacement method”. According to the realization probability and dispersion degree of the planned target combined with the risk grade evaluation matrix, the planning target evaluation risk grade was implemented. Moreover, the planning unit risk grade evaluation was obtained at different stages. Regarding the specific production capacity conditions in gas wells (horizontal and vertical wells) and gas reservoir water invasion – the probability method with Monte Carlo stochastic simulation was used to calculate the production and water invasion volumes. The established decision-making risk technology for gas reservoir development, along with the associated supporting procedures can be used to evaluate the risks of reservoir development planning, production, and water invasion.

Framing Effects in Ambiguous Risk Decision Making

2011 ◽  
Author(s):  
Paul Whitney ◽  
John M. Hinson ◽  
Peter J. Rosen
Keyword(s):  
Decision Making ◽  
Framing Effects ◽  
Risk Decision

scholarly journals Development of a prognostic tool: based on risk factors for tooth loss after active periodontal therapy

2021 ◽  
Author(s):  
Sonja Rahim-Wöstefeld ◽  
Dorothea Kronsteiner ◽  
Shirin ElSayed ◽  
Nihad ElSayed ◽  
Peter Eickholz ◽  
...  
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Tooth Loss ◽  
Treatment Plan ◽  
Periodontal Therapy ◽  
Outcome Variable ◽  
Individual Treatment ◽  
Risk Indicator ◽  
Related Factors ◽  
Prognostic Tool

Abstract Objectives The aim of this study was to develop a prognostic tool to estimate long-term tooth retention in periodontitis patients at the beginning of active periodontal therapy (APT). Material and methods Tooth-related factors (type, location, bone loss (BL), infrabony defects, furcation involvement (FI), abutment status), and patient-related factors (age, gender, smoking, diabetes, plaque control record) were investigated in patients who had completed APT 10 years before. Descriptive analysis was performed, and a generalized linear-mixed model-tree was used to identify predictors for the main outcome variable tooth loss. To evaluate goodness-of-fit, the area under the curve (AUC) was calculated using cross-validation. A bootstrap approach was used to robustly identify risk factors while avoiding overfitting. Results Only a small percentage of teeth was lost during 10 years of supportive periodontal therapy (SPT; 0.15/year/patient). The risk factors abutment function, diabetes, and the risk indicator BL, FI, and age (≤ 61 vs. > 61) were identified to predict tooth loss. The prediction model reached an AUC of 0.77. Conclusion This quantitative prognostic model supports data-driven decision-making while establishing a treatment plan in periodontitis patients. In light of this, the presented prognostic tool may be of supporting value. Clinical relevance In daily clinical practice, a quantitative prognostic tool may support dentists with data-based decision-making. However, it should be stressed that treatment planning is strongly associated with the patient’s wishes and adherence. The tool described here may support establishment of an individual treatment plan for periodontally compromised patients.

The effect of social reference points on self-other risk decision-making

2021 ◽  
Author(s):  
Dawei Wang ◽  
Mengmeng Zhou ◽  
Liping Zhu ◽  
Yixin Hu ◽  
Yuxi Shang
Keyword(s):  
Decision Making ◽  
Reference Points ◽  
Social Reference ◽  
Risk Decision

scholarly journals Quantitative study on natural gas production risk of Carboniferous gas reservoir in eastern Sichuan

2021 ◽  
Author(s):  
Guo Yu ◽  
Haitao Li ◽  
Yanru Chen ◽  
Linqing Liu ◽  
Chenyu Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Natural Gas ◽  
Gas Production ◽  
Probability Method ◽  
Gas Reservoir ◽  
Production Risk ◽  
Probability Interval ◽  
Natural Gas Production ◽  
Stable Production

AbstractQuantifying natural gas production risk can help guide natural gas exploration and development in Carboniferous gas reservoirs. In this study, the Monte Carlo probability method is used to obtain the probability distribution and growth curve of each production risk factor and production in a Carboniferous gas reservoir in eastern Sichuan. In addition, the fuzzy comprehensive evaluation method is used to conduct the sensitivity analysis of the risk factors, and the natural gas production and realization probability under different risk factors are obtained. The research results show that: (1) the risk factor–production growth curve and probability distribution are calculated by the Monte Carlo probability method. The average annual production under the stable production stage under different realization probabilities is obtained. The maximum probability range of annual production is $$\left( {43.43 - 126.35} \right) \times 10^{8} {\text{m}}^{3} /{\text{year}}$$ 43.43 - 126.35 × 10 8 m 3 / year , and the probability range is 14.59–92.88%. (2) The risk factor sensitivity analysis is significantly affected by the probability interval. In the entire probability interval, the more sensitive risk factors are the average production of the kilometer-deep well (D) and the production rate in the stable production stage (A). During the exploration and development of natural gas, these two risk factors can be adjusted to increase production.

Risky Business: An Integrated Institutional Theory for Understanding High-Risk Decision Making in Higher Education

2018 ◽  
Vol 88 (1) ◽  
pp. 53-80 ◽  
Author(s):  
LAUREN A. TURNER ◽  
A. J. ANGULO
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
High Risk ◽  
Institutional Theory ◽  
Integrated Model ◽  
Organizational Strategies ◽  
Recent Trends ◽  
Internal Pressures ◽  
Higher Education Organizations ◽  
Risk Decision

Lauren A. Turner and A. J. Angulo explore how institutional theory can be applied to explain variance in higher education organizational strategies. Given strong regulatory, normative, and cultural-cognitive pressures to conform, they ask, why do some colleges engage in high-risk decision making? To answer this, they bring together classic and contemporary approaches to institutional theory and propose an integrated model for understanding outlier higher education strategies. The integrated model offers a heuristic for analyzing external and internal pressures that motivate colleges to implement nontraditional strategies. Through an analysis of recent trends among outlier colleges and their approaches to the Scholastic Aptitude Test, Turner and Angulo contextualize the model and consider its potential for understanding why higher education organizations adopt characteristics that differentiate them from their peers.

Sign in / Sign up

Export Citation Format

Share Document