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Presented in an easy-to-use format, this second edition of Formulas and Calculations for Drilling Operations is a quick reference for day-to-day work out on the rig. It also serves as a handy study guide for drilling and well control certification courses. Virtually all the mathematics required on a drilling rig is here in one convenient source, including formulas for pressure gradient, specific gravity, pump, output, annular velocity, buoyancy factor, and many other topics. Whether open on your desk, on the hood of your truck at the well, or on an offshore platform, this is the only book available that covers the gamut of the formulas and calculations for petroleum engineers that have been compiled over decades. Some of these formulas and calculations have been used for decades, while others are meant to help guide the engineer through some of the more recent breakthroughs in the industry's technology, such as hydraulic fracturing and enhanced oil recovery. There is no other source for these useful formulas and calculations that is this thorough. An instant classic when the first edition was published, the much-improved revision is even better, offering new information not available in the first edition, making it as up-to-date as possible in book form. Truly a state-of-the-art masterpiece for the oil and gas industry, if there is only one book you buy to help you do your job, this is it!

As massive underground projects have become popular in dense urban cities, a problem has arisen: which model predicts the best for Tunnel Boring Machine (TBM) performance in these tunneling projects? However, performance level of TBMs in complex geological conditions is still a great challenge for practitioners and researchers. On the other hand, a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction schedule. The performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine specifications. The previously-proposed intelligent techniques in this field are mostly based on a single or base model with a low level of accuracy. Hence, this study aims to introduce a hybrid random forest (RF) technique optimized by global harmony search with generalized opposition-based learning (GOGHS) for forecasting TBM advance rate (AR). Optimizing the RF hyper-parameters in terms of, e.g., tree number and maximum tree depth is the main objective of using the GOGHS-RF model. In the modelling of this study, a comprehensive database with the most influential parameters on TBM together with TBM AR were used as input and output variables, respectively. To examine the capability and power of the GOGHS-RF model, three more hybrid models of particle swarm optimization-RF, genetic algorithm-RF and artificial bee colony-RF were also constructed to forecast TBM AR. Evaluation of the developed models was performed by calculating several performance indices, including determination coefficient (R2), root-mean-square-error (RMSE), and mean-absolute-percentage-error (MAPE). The results showed that the GOGHS-RF is a more accurate technique for estimating TBM AR compared to the other applied models. The newly-developed GOGHS-RF model enjoyed R2 = 0.9937 and 0.9844, respectively, for train and test stages, which are higher than a pre-developed RF. Also, the importance of the input parameters was interpreted through the SHapley Additive exPlanations (SHAP) method, and it was found that thrust force per cutter is the most important variable on TBM AR. The GOGHS-RF model can be used in mechanized tunnel projects for predicting and checking performance.

Tunnel Boring Machines (TBMs) are vital for tunnel and underground construction due to their high safety and efficiency. Accurately predicting TBM operational parameters based on the surrounding environment is crucial for planning schedules and managing costs. This study investigates the effectiveness of tree-based machine learning models, including Random Forest, Extremely Randomized Trees, Adaptive Boosting Machine, Gradient Boosting Machine, Extreme Gradient Boosting Machine (XGBoost), Light Gradient Boosting Machine, and CatBoost, in predicting the Penetration Rate (PR) of TBMs by considering rock mass and material characteristics. These techniques are able to provide a good relationship between input(s) and output parameters; hence, obtaining a high level of accuracy. To do that, a comprehensive database comprising various rock mass and material parameters, including Rock Mass Rating, Brazilian Tensile Strength, and Weathering Zone, was utilized for model development. The practical application of these models was assessed with a new dataset representing diverse rock mass and material properties. To evaluate model performance, ranking systems and Taylor diagrams were employed. CatBoost emerged as the most accurate model during training and testing, with R2 scores of 0.927 and 0.861, respectively. However, during validation, XGBoost demonstrated superior performance with an R2 of 0.713. Despite these variations, all tree-based models showed promising accuracy in predicting TBM performance, providing valuable insights for similar projects in the future.

This paper introduces a new stabilization algorithm to Lagrangian particle methods for the coupled thermal mechanical analysis in the friction drilling simulation. Different from the conventional penalty method which utilizes a direct smoothing of velocity fields in the weak formulation, the proposed algorithm introduces the smoothed velocity fields through linear momentum equations for stabilization. Particle approximations are used for the discretization of coupled thermal mechanical discrete equations. The coupled system is solved by the explicit and staggered time marching scheme. In comparison to the conventional penalty method which requires at least one extra integration point for stabilization, the proposed algorithm needs only one integration point per particle in computation. The essential features of linear and angular momentum conservations are preserved in the explicit dynamic analysis. A bridging scheme is also developed to couple the particle formulation with finite element formulation for practical industrial applications. Several benchmark tests are performed to examine the effectiveness of this new method. Furthermore, a friction drilling application is studied, and the results are compared with the experimental data.

PurposeDespite the many advantages this type of equipment offers, there are still some major drawbacks. Linear cutting machine (LCM) cannot accurately simulate the true rock-cutting process as 1. it does not account for the circular path along which tunnel boring machine (TBM) disk cutters cut the tunnel face, 2. it does not accurately model the position of a disk cutter on the cutterhead, 3. it cannot perfectly replicate the rotational speed of a TBM. To enhance the knowledge of these issues and in order to mimic the real rock-cutting process, a new lab testing equipment was developed by Hyundai Engineering and Construction.Design/methodology/approachA new testing machine called rotary cutting machine (RCM) is designed to simulate the excavation process of hard-rock TBMs and includes features such as TBM cutterhead, RPM simulation, constant normal force mode and constant penetration rate mode. Two sets of tests were conducted on Hwandeung granite using different disk cutter sizes to analyze the cutting forces in various excavation modes. The results are analyzed using statistical analysis and dimensional analysis. A new model is generated using dimensional analysis, and its results are compared against the results of actual cases.FindingsThe effectiveness of the new RCM test was demonstrated in its ability to apply various modes of excavation. Initial analysis of chip size revealed that the thickness of the chips is largely dependent on the cutter spacing. Tests with varying RPM showed that an increase in RPM results in an increase in the normal force and rolling force. The cutting coefficient (CC) demonstrated a linear correlation with penetration. The optimal specific energy is achieved at an S/p ratio of around 15. However, a slightly lower S/p ratio can also be used in the design if the cutter specifications permit. A dimensional analysis was utilized to develop a new RCM model based on the results from approximately 1200 tests. The model's applicability was demonstrated through a comparison of TBM penetration data from 26 tunnel projects globally. Results indicated that the predicted penetration rates by the RCM test model were in good agreement with actual rates for the majority of cases. However, further investigation is necessary for softer rock types, which will be conducted in the future using concrete blocks.Originality/valueThe originality of the research lies in the development of Hyundai Engineering and Construction’s advanced full-scale laboratory rotary cutting machine (RCM), which accurately replicates the excavation process of hard-rock tunnel boring machines (TBMs). The study provides valuable insights into cutting forces, chip size, specific energy, RPM and excavation modes, enhancing understanding and decision-making in hard-rock excavation processes. The research also presents a new RCM model validated against TBM penetration data, demonstrating its practical applicability and predictive accuracy.

The efficient exploitation of marine oil and gas resources holds significant potential to mitigate the current severe energy crisis. Regrettably, incidents, such as gas kick and even blowouts, can significantly impact normal development activities. The displacement kill method is one effective strategy for well control in deep-water areas. In this study, the detailed mathematical method for determining kill parameters involved in the kill operation by using the displacement kill method was proposed. Of course, this includes both cases: one where the kill fluid leaks during the kill process and another where no leakage occurs. Meanwhile, its applicability was verified through comparison with experimental results. Then, evolution characteristics of kill parameters, when killing fluid leakage occurs and when it does not occur, were analyzed. Finally, factors, such as pit gain and shut-in casing pressure, affecting the kill parameters of kill operation, were explored. It was found that the experimental and calculated results show great similarity, although there are slight differences between them. The total kill time in the simulation is 44 s shorter than that in the verification experiment. This indicates that the model established in this study is suitable for simulating the process of kill operation using the displacement kill method. In addition, the investigation results show that leakage of kill fluid increases the difficulty of the kill operation and prolongs the operation time. The number of kill cycles in the presence of kill fluid leakage is one more than that when there is no fluid leakage, resulting in an additional 70 min of total duration. Furthermore, the increase in pit gain and the rise in shut-in casing pressure can also pose challenges to the kill operations. The total kill time will be extended by 164 min when the mud pit gain increases from 20 m3 to 50 m3. The number of kill cycles rises by two when the shut-in casing pressure is increased from 5 MPa to 20 MPa. To ensure the safety of the drilling operation in abnormally high-pressure reservoirs, it is crucial to monitor parameters such as casing pressure during the drilling process and timely well control measures.

In this paper, the field-enriched finite element method is proposed for simulating three-dimensional crack propagation, in which the influences of three-dimensional crack on the physical fields of computational model are described by enriching the field variable on the nodes. Then, through a benchmark example, it is found that under different mesh densities, the convergence rate of the stress intensity factor and energy norm error obtained by the field-enriched finite element method is faster than that of the traditional finite element method. Moreover, the field-enriched finite element method can calculate the stress intensity factor which is basically close to the precision of the extended finite element method and the analytical solution. Finally, comparing with the other numerical results or experimental results on three numerical examples, it is found that the proposed method can effectively and accurately simulate the three-dimensional crack propagation process under different loading conditions.

Tunnel construction is susceptible to accidents such as loosening, deformation, collapse, and water inrush, especially under complex geological conditions like dense fault areas. These accidents can cause instability and damage to the tunnel. As a result, it is essential to conduct research on tunnel construction and grouting reinforcement technology in fault fracture zones to address these issues and ensure the safety of tunnel excavation projects. This study utilized the Xianglushan cross-fault tunnel to conduct a comprehensive analysis on the construction, support, and reinforcement of a tunnel crossing a fault fracture zone using the three-dimensional finite element numerical method. The study yielded the following research conclusions: The excavation conditions of the cross-fault tunnel array were analyzed to determine the optimal construction method for excavation while controlling deformation and stress in the surrounding rock. The middle partition method (CD method) was found to be the most suitable. Additionally, the effects of advanced reinforcement grouting on the cross-fault fracture zone tunnel were studied, and the optimal combination of grouting reinforcement range (140°) and grouting thickness (1 m) was determined. The stress and deformation data obtained from on-site monitoring of the surrounding rock was slightly lower than the numerical simulation results. However, the change trend of both sets of data was found to be consistent. These research findings provide technical analysis and data support for the construction and design of cross-fault tunnels.

The adaptability of an earth pressure balance (EPB) tunnel boring machine (TBM) to complex geological strata needs to be evaluated when a tunnel project is set up. It is helpful for better design and more suitable technical parameters of the machine. Because the factors that influence adaptability are numerous and interrelated, their effects also differ; hence, a quantitative assessment of adaptability is generally difficult. In the present study, a method for quantitatively evaluating the excavation adaptability of an EPB TBM was developed using an analytic hierarchy process (AHP) and fuzzy comprehensive evaluation. The method first involves an initial selection of factors that may influence tunnelling. Based on the expert questionnaire and their influence weights determined by AHP, the 10 evaluation indexes from 25 primary indexes were selected to establish the evaluation index system (EIS) including a target, criteria, and index level. Fuzzy membership functions are then derived one after another based on the effect of each evaluation index on the EBP TBM tunnelling process. A fuzzy mathematical method was finally presented to determine the adaptability of an EPB TBM excavation performance. The proposed method was applied to two special sections of diameter 6.98 m excavated by two EPB TBMs in the Shenzhen Metro Line 11 project. The geological exploration shows that these two tunnel sections pass through typical composite strata in Shenzhen. The determined adaptability grades of the EPB TBMs used for composite strata were confirmed by the actual tunnel excavation. It indicates that the developed method is reasonable and useful to evaluate tunnelling adaptability of EPB TBM.

In tunnel construction, predicting the roughness of discontinuity is significant for preventing the collapse of the excavation face. However, currently, we are unable to use a parameter with invariant properties to quantify and predict the roughness of discontinuity. Fractal dimension D is one such parameter that be used to characterize the roughness of discontinuity. The study proposes a new method to predict the roughness of discontinuity from the fractal dimension D of outcrops. The measurement method of the coordinates of outcrops is firstly summarized, and the most suitable method of calculating fractal dimension D is then provided. For characterizing the spatial variability of fractal dimension D, the random field of fractal dimension D is discretized, and the prediction model is then established based on Bayesian theory. The proposed method is applied to one tunnel for predicting the roughness of discontinuity, and the results indicate that the relative errors of prediction are less than 1.5%. The sensitivities of correlation function and discontinuity size are analyzed. It is found that the different correlation functions have no obvious effect on the prediction results, and the proposed method is well applied to relatively large sizes of discontinuity.