The Method of Oilfield Development Risk Forecasting and Early Warning Using Revised Bayesian Network

Abstract

Oilfield development aiming at crude oil production is an extremely complex process, which involves many uncertain risk factors affecting oil output. Thus, risk prediction and early warning about oilfield development may insure operating and managing oilfields efficiently to meet the oil production plan of the country and sustainable development of oilfields. However, scholars and practitioners in the all world are seldom concerned with the risk problem of oilfield block development. The early warning index system of blocks development which includes the monitoring index and planning index was refined and formulated on the basis of researching and analyzing the theory of risk forecasting and early warning as well as the oilfield development. Based on the indexes of warning situation predicted by neural network, the method dividing the interval of warning degrees was presented by “3σ” rule; and a new method about forecasting and early warning of risk was proposed by introducing neural network to Bayesian networks. Case study shows that the results obtained in this paper are right and helpful to the management of oilfield development risk.

A Connectionist Model for Dynamic Economic Risk Analysis of Hydrocarbons Production Systems

“…Zhong et al. (2016) also achieved a similar outcome in their work. One of the key tasks in the development of the logical model is the construction of the conditional probabilities table (CPT).…”

“…The statistical parameters are expressed by Equations (5) and (6) (Adedigba, Khan, & Yang, 2017c). Applications of ANN models in different engineering cases are well‐documented in the literature (Adedigba et al., 2017b; Kim, Shin, Yu, Kim, & Hwang, 2019; Kimaev & Ricardez‐Sandoval, 2019; Zendehboudi et al., 2018 ; Zhong et al., 2016). $$\begin{equation}f\left( x \right) = \frac{1}{{1 + {e^{ - x}}}}\end{equation}$$in which, $$f$$ stands for the activation function and $$x$$ represents a variable.…”

“…The detailed procedure is given in Section 3.3. The EWIS principles are based on the procedures of risk identification and assessment (Horner, Castle, & Rodgers, 2011; Zhong et al., 2016).…”

“…The statistical parameters are expressed by Equations ( 5) and ( 6) (Adedigba, Khan, & Yang, 2017c). Applications of ANN models in different engineering cases are well-documented in the literature (Adedigba et al, 2017b;Kim, Shin, Yu, Kim, & Hwang, 2019;Kimaev & Ricardez-Sandoval, 2019;Zendehboudi et al, 2018 ;Zhong et al, 2016).…”

Contribution of Risk Perception and Communication in Aviation Safety Events

“…Although the former finding indicates successful system interventions over time, the latter suggests a possible underestimation or underresearch of the respective factors. Therefore, although aviation organizations are expected to follow a rigid risk management framework focusing on numerical/parametric data ( 8 ), a pragmatic approach to real-time risk management at the operator level could be more effective than simulated forecasts ( 85 ).…”