The accurate and frequent measurement of the drilling fluid’s rheological properties is essential for proper hydraulic management. It is also important for intelligent drilling, providing drilling fluid data to establish the optimization model of the rate of penetration. Appropriate drilling fluid properties can improve drilling efficiency and prevent accidents. However, the drilling fluid properties are mainly measured in the laboratory. This hinders the real-time optimization of drilling fluid performance and the decision-making process. If the drilling fluid’s properties cannot be detected and the decision-making process does not respond in time, the rate of penetration will slow, potentially causing accidents and serious economic losses. Therefore, it is important to measure the drilling fluid’s properties for drilling engineering in real time. This paper summarizes the real-time measurement methods for rheological properties. The main methods include the following four types: an online rotational Couette viscometer, pipe viscometer, mathematical and physical model or artificial intelligence model based on a Marsh funnel, and acoustic technology. This paper elaborates on the principle, advantages, limitations, and usage of each method. It prospects the real-time measurement of drilling fluid rheological properties and promotes the development of the real-time measurement of drilling rheological properties.

In gas drilling operations, the rate of penetration (ROP) parameter has an important influence on drilling costs. Prediction of ROP can optimize the drilling operational parameters and reduce its overall cost. To predict ROP with satisfactory precision, a stacked generalization ensemble model is developed in this paper. Drilling data were collected from a shale gas survey well in Xinjiang, northwestern China. First, Pearson correlation analysis is used for feature selection. Then, a Savitzky-Golay smoothing filter is used to reduce noise in the dataset. In the next stage, we propose a stacked generalization ensemble model that combines six machine learning models: support vector regression (SVR), extremely randomized trees (ET), random forest (RF), gradient boosting machine (GB), light gradient boosting machine (LightGBM) and extreme gradient boosting (XGB). The stacked model generates meta-data from the five models (SVR, ET, RF, GB, LightGBM) to compute ROP predictions using an XGB model. Then, the leave-one-out method is used to verify modeling performance. The performance of the stacked model is better than each single model, with R² = 0.9568 and root mean square error = 0.4853 m/h achieved on the testing dataset. Hence, the proposed approach will be useful in optimizing gas drilling. Finally, the particle swarm optimization (PSO) algorithm is used to optimize the relevant ROP parameters.

To overcome the negative impact on the rheological and filtration loss properties of drilling fluids caused by elevated temperature and salts contamination, which are common in ultradeep or geothermal drilling operations, it is imperative to develop highly efficient additives used in the water-based drilling fluid. In this study, a zwitterionic copolymer P (AM/DMC/AMPS/DMAM, ADAD) was synthesized by using acrylamide (AM), cationic monomer methacrylatoethyl trimethyl ammonium chloride (DMC), anionic monomer 2-acrylamide-2-methyl propane sulfonic acid (AMPS), and N,N-dimethylacrylamide (DMAM) through free radical copolymerization. The copolymer was characterized by ¹H Nuclear Magnetic Resonance (NMR), Fourier transform infrared spectroscopy (FTIR), elemental analysis, thermogravimetric analysis (TGA), and zeta potential. The rheological behavior, filtration properties, and the performance exposure to salt or calcium contamination in water-based drilling fluid were investigated. The bentonite/polymer suspension showed improved rheological and filtration properties even after aging at 160 °C or a high concentration of salt and calcium. The filtration loss can be greatly reduced by more than 50% (from 18 mL to 7 mL) by the inclusion of 2.0 wt% copolymer, while a slight increase in the filtrate loss was observed even when exposed to electrolyte contamination. Particle size distribution and zeta potential further validate the idea that zwitterionic copolymer can greatly improve the stability of base fluid suspension through positive group enhanced anchoring on the clay surface and repulsion force between negative particles. Moreover, this study can be directed towards the design and application of zwitterionic copolymer in a water-based drilling fluid.

Electropulse rock breaking has wide application prospects in hard rock drilling and ore breaking. At present, there are no suitable physical mathematical models that describe electropulse boring (EPB) processes under confining pressures. In this paper, a high‐voltage electropulse breakdown damage model is established for granite, which includes three submodels. It considers electric field distortions inside the rock, and an electric field distribution coefficient is introduced in the electro‐breakdown model. A shock‐wave model is also constructed and solved. To simulate the heterogeneity of rocks, EPB rock breaking in deep environments is simulated using the two‐dimensional Particle Flow Code (PFC2D) program. The solved shock wave is loaded into the model, and confining pressure is applied by the particle servo method. An artificial viscous boundary is used in the numerical simulation model. Using this approach, a complete numerical simulation of electropulse granite breaking is achieved. Breakdown strength and the influences of physical and mechanical parameters on it are also obtained. Time‐varying waveforms of electrical parameters are obtained, and the effect of confining pressure on EPB is also described.