Research and Application of Wellbore Stability Based on Quantitative Risk Analysis

The weakly consolidated sands of Guantao Formation in Bohai has shallow buried depth, low degree of compaction and frequent wellbore collapse. The research on wellbore stability is very important for the efficient development of this kind of low resistivity reservoir. This study involves many parameters, including rock modulus, rock strength, in-situ stress and other parameters. And the uncertainty of these parameters is difficult to avoid. Traditional methods usually ignore the influence of the uncertainty of model parameters on the fracture pressure and collapse pressure, and the prediction results are often difficult to meet the field operation requirements. Based on the constitutive equation and failure criterion of rock deformation, a classical wellbore stability model is established. Using data from core experiments, field tests, and logging evaluations, the mean, maximum, and minimum values of the model input parameters are statistically obtained. And the sensitivity analysis of the model parameters is carried out to identify the key parameters of the model. According to the probability density function (PDF) of the model parameters, Monte Carlo simulation technology is used for random sampling. Then tens of thousands of random sampling results are substituted into the wellbore stability model to calculate the probability density functions (PDFs) of fracture pressure and collapse pressure. Sensitivity analyses show that maximum horizontal stress, internal friction angle, cohesion and Poisson’s ratio are the major variables to determine collapse pressure. And maximum and minimum horizontal stresses, Poisson’s ratio are the most critical parameters in fracture pressure evaluation. Finally, an uncertainty analysis is presented in the form of probabilistic graphs. The safe mud density window is obtained as a probability function of the risk of borehole instability. This provides a reasonable range of drilling fluid density for field operators. When the reliability of input parameters is high, any value in the interval of [P50, P90] is selected as the prediction result. When the uncertainty of input parameters is high, P90 is used as the prediction result. In this paper, Monte Carlo simulation is used to quantify the uncertainty of each input parameter, and the risk of borehole collapse and leakage is quantitatively expressed in the form of probability. It can provide reliable reference for drilling fluid density design and reduce the risk of drilling operation.