The decline curve analysis (DCA) technique is the simplest, fastest, least computationally demanding, and least data-required reservoir forecasting method. Assuming that the decline rate of the initial production data will continue in the future, the estimated ultimate recovery (EUR) can be determined at the end of the well/reservoir lifetime based on the declining mode. Many empirical DCA models have been developed to match different types of reservoirs as the decline rate varies from one well/reservoir to another. In addition to the uncertainties related to each DCA model’s performance, structure, and reliability, any of them can be used to estimate one deterministic value of the EUR, which, therefore, might be misleading with a bias of over- and/or under-estimation. To reduce the uncertainties related to the DCA, the EUR could be assumed to be within a certain range, with different levels of confidence. Probabilistic decline curve analysis (pDCA) is the method used to generate these confidence intervals (CIs), and many pDCA approaches have been introduced to reduce the uncertainties that come with the deterministic DCA. The selected probabilistic type of analysis (i.e., frequentist or Bayesian), the used DCA model(s), the type and the number of wells, the sampling technique of the data or the model’s parameters, and the parameters themselves undergo a probability distribution, and these are the main differences among all of these approaches and the factors that determine how each approach can quantify the uncertainties and mitigate them. In this work, the Bayesian and frequentist approaches are deeply discussed. In addition, the uncertainties of DCA are briefly discussed. Further, the bases of the different probabilistic analyses are explained. After that, 15 pDCA approaches are reviewed and summarized, and the differences among them are stated. The study concludes that Bayesian analysis is generally more effective than frequentist analysis, though with narrower CIs. However, the choice of DCA model and sampling algorithm can also affect the bounds of the CIs and the calculation of the EUR. Moreover, the pDCA approach is recommended for quantifying uncertainties in DCA, with narrower CIs that indicate greater effectiveness. However, the computational time and the number of iterations in sampling are also considered critical factors. That is why various assumptions and modifications have been made in the pDCA approaches, including the assumption of a certain probability distribution for the sampled parameters to improve their reliability of reserve estimation. The motivation behind this research was to present a full state-of-the-art review of the pDCA and the latest developments in this area of research.

Wellbore stability in extreme drilling environments remains a critical challenge. This study advances the understanding of these complexities through a comprehensive numerical modeling approach. By incorporating thermal, chemical, and hydraulic effects, four refined models were developed to simulate wellbore behavior under high pressures and temperatures. A comparative analysis of four failure criteria and a detailed investigation into the impact of fluid properties on pore pressure and stress distribution provide novel insights. The results indicate that pressure distribution and stress variations around the wellbore are significantly influenced by poroelastic, thermal, and chemical effects. The poroelastic effect increases pressure due to overbalanced drilling conditions, while thermal effects vary with fluid temperature, leading to notable pressure changes. Chemical effects are significant, with lower salinity mud increasing pore pressure and higher salinity decreasing it. Thermal effects primarily dominate stress distribution, altering radial, tangential, and axial stresses, with tangential stresses peaking in the direction of minimum horizontal stress. Collapse area predictions suggest that Mohr-Coulomb and Drucker-Prager criteria predict larger collapse areas compared to Mogi-Coulomb and Modified-Lade criteria, indicating a more conservative approach. Poroelastic effects slightly enlarge collapse areas due to increased pore pressure, while thermal effects reduce collapse areas with cooling and increase them with heating. Higher salinity mud improves formation stability by enhancing effective stress and reducing pore pressure. The results demonstrate that using higher salinity mud enhances formation stability and that careful management of temperature can mitigate stress variations and collapse risks. Regular monitoring and adjustments based on wellbore stability models are essential for optimizing performance and safety in drilling operations. The findings reveal that optimizing mud salinity and carefully managing temperature can effectively enhance formation stability, which offers practical guidelines for mitigating wellbore risks and optimizing drilling operations in challenging formations.

Prediction of the wellbore fluids and formation temperatures is crucial during drilling operation, especially for high temperature wells, such as geothermal applications. This work presents the applications of an improved comprehensive drilling simulator for predicting the wellbore system temperature during the drilling process. A fully transient numerical model of the wellbore temperature is developed for drilling and geothermal production applications. The model describes the dynamic behaviour of the thermal state of the wellbore during circulation and static conditions. The developed model is implemented with the commercial virtual drilling simulator through an application programming interface. This implementation allows the coupling of the thermal model with other physical models, which leads to more advanced and realistic simulations. The model has been previously validated through a direct comparison with field data from geothermal well located in the Hanover area in Germany. The results showed a good agreement between the predicted outlet fluid temperature and the measured one. Furthermore, an analysis of the effect of various parameters on the wellbore system temperature is performed. This analysis showed the impact of these parameters on the wellbore temperature profile including the critical areas such as the casing setting point and bottom hole assembly. This information may lead to enhancing the wellbore stability by monitoring the thermal stresses, especially in high-temperature wells. Moreover, predicting the drill bit temperature can result in increasing the lifetime of the bit by adjusting the operating conditions to keep the bit temperature within the specified range. Based on these results, the enhanced drilling simulator with the transient temperature model showed to be a suitable tool for effective well planning. Cited as: Abdelhafiz, M. M., Oppelt, J., Mahmoud, O., Hegele, L. A. Effect of drilling and wellbore geometry parameters on wellbore temperature profile: Implications for geothermal production. Advances in Geo-Energy Research, 2023, 8(3): 170-180. https://doi.org/10.46690/ager.2023.06.04