Uncertainty-Based Approach for Predicting the Operating Window in UBO Well Design

Abstract

Summary Underbalanced operations (UBO) are carried out to bypass drilling challenges that could be difficult to resolve by use of conventional drilling techniques. Steady-state multiphase-flow models are used to construct underbalanced-drilling operational windows. These advanced software models are deterministically formulated. It is known that some of the model input parameters, such as the multiphase-flow parameters, friction factors, and reservoir productivity, are subject to uncertainties. Failures to capture these variabilities may introduce some error in the model prediction, resulting in poor well planning and implementation. The purpose of this work is to implement probabilistic modeling of underbalanced drilling by use of a simple steady-state two-phase model. Both predefined uncertain and fixed factors serve as inputs to a pre-existing deterministic model. By applying Monte Carlo simulations, the model predicts outputs that follow a statistical distribution. A sensitivity analysis is conducted to determine the input factor that is most responsible for the uncertainty in the predicted bottomhole pressure (BHP). The results demonstrate that uncertainty modeling can improve underbalanced-drilling design and operations. A more realistic operational window is obtained, ensuring that underbalanced condition is maintained throughout the target section. With a better understanding of uncertainties and the corresponding impacts, well planners can make better decisions regarding well design criteria and safe operational conditions, and avoid huge economic consequences.

Risk Assessment Method for Analyzing Borehole Instability Considering Formation Heterogeneity

“…The larger the overlap area, the lower the probability of borehole stability. At the intersection of the blue curve and the red curve, the drilling fluid density is 1.61 g/cm 3 , and the probability that the borehole wall will not collapse or break is 95.895%. The stability and reliability of the borehole wall are the highest at this drilling fluid density, but the safety density window is extremely narrow.…”

“…Borehole instability is one of the key factors affecting borehole rules and comprehensive drilling benefits. Statistics show that borehole instability causes losses of USD 500~600 million in the worldwide oil industry every year [1][2][3][4]. It is one of the world's most concerned problems to drilling workers at home and abroad, and it is also an important matter that scientific and technological workers have been making unremitting efforts to tackle [5][6][7][8][9][10].…”

“…The estimated probability of borehole stability can reach 91~98%, and the calculated results are basically consistent with the actual situation. Considering the uncertainty of model input parameters, Udegbunam et al [3] used Monte Carlo simulation to study the impact of probabilistic input parameters on borehole stability, and the results showed that uncertainty modeling could obtain a more realistic operating window and improve underbalanced drilling design and operations. Hilgedick et al [30] used the Monte Carlo random sampling method to calculate the numerical solution of the risk probability of borehole instability, and compared it to the traditional borehole stability coefficient.…”

Uncertainty Evaluation of Safe Mud Weight Window Utilizing the Reliability Assessment Method

“…Regarding the choice of random variable distributions, some of the probability distributions normally used in wellbore stability analysis include the uniform distribution, triangular distribution, lognormal distribution, Gamma distribution, Beta distribution, and Weibull distribution [30]. From an engineering perspective, the normal distribution is the preferred choice for wellbore stability problems, due to the distribution functions are mostly normally distributed [38,39]. It should be noticed that the random variable distributions used in this work are based on assumption, but the choice of random variable distributions should be revisited.…”

A Methodology for Classifying Operating Regimes in Underbalanced-Drilling Operations

“…Appendix A: The DFM The following is a recap of the formulation described by Aarsnes et al (2014b) and Udegbunam et al (2014) on the basis of the work by Evje and Fjelde (2002).…”