Search Results (46)

Accurate estimation of downhole weight on bit (DWOB) is important for drilling parameter optimization and safe drilling in extended-reach horizontal wells. However, DWOB is difficult to obtain continuously because surface weight on bit (SWOB) is attenuated by drill-string friction, wellbore trajectory, and borehole-wall contact. To address this problem, a physics-informed convolutional neural network combined with bidirectional gated recurrent unit (CNN-BiGRU) prediction model optimized by the whale optimization algorithm (WOA) is proposed using surface sensor data and downhole measurement-while-drilling (MWD) measurements. The model first uses a one-dimensional CNN to extract local features from drilling parameters along the measured-depth direction and then employs a BiGRU to capture depth-series dependencies. Meanwhile, a drill-string frictional attenuation relationship is embedded into the loss function as a physical prior, and WOA is used to optimize network hyperparameters and the physics-constrained weight. Field data from a horizontal well were used for validation. The proposed model achieved a coefficient of determination (R²)of 0.9245 on the test set, with root mean square error (RMSE), mean absolute error (MAE), and mean relative error (MRE) values of 0.1856, 0.1135, and 0.0124, respectively. The results demonstrate that the proposed data–physics hybrid framework improves the accuracy and physical consistency of DWOB prediction. Full article

Efficiently and accurately converting floating-point numbers to decimal strings remains a fundamental challenge in numerical computation, data serialization, and human–computer interaction. While modern algorithms such as Ryū, Dragonbox, and Schubfach rigorously satisfy the Steele–White criteria for correctness and minimal output length, their performance is frequently constrained by branch mispredictions, high-precision multiplication overhead, and suboptimal utilization of instruction-level parallelism. This paper introduces xjb, a novel floating-point–string conversion algorithm derived from Schubfach that systematically overcomes these bottlenecks. By restructuring the core computation to reduce instruction dependencies, adopting branchless decision logic, and exploiting SIMD instruction sets for decimal-to-ASCII formatting, xjb delivers state-of-the-art throughput across diverse hardware platforms. The algorithm requires only a single 64-by-128-bit multiplication for IEEE 754 binary64 conversions and a single 64-by-64-bit multiplication for binary32, drastically decreasing arithmetic complexity. Extensive benchmarking on AMD R7-7840H and Apple M1/M5 processors demonstrates that xjb consistently outperforms leading contemporary implementations. Notably, on the Apple M5, xjb achieves speedups of approximately 20% and 136% for binary64 and binary32 conversions, respectively, when compared to the highly optimized zmij library. The algorithm is fully compliant with the Steele–White principle; exhaustive validation over the entire binary32 space and extensive random testing across the binary64 range confirm both its theoretical soundness and practical robustness. Full article

This research-related study examines the relevance of mud pulse telemetry (MPT) systems and their intersection with drilling performance, focusing on data transmission signal propagation performance and overall operation under different drilling parameters conditions, with an additional focus on drilling fluid flow rate and downhole pressure conditions. The novelty of this study lies in the investigation of adjustments to drilling operating parameters that could potentially improve the transmission of telemetry signals during drilling, in real time, without requiring mechanical or functional modifications to the MPT system itself. Improvements on transmission performance in situations where the data rate may be limited are also addressed, presenting an alternative through possible propagation velocity improvements to counterbalance it. A detailed chronological technical scientific literature review details important parts on analyses of pressure pulse propagation velocities focused on data transmission. A systematic experimental approach was developed and put into practice to evaluate the MPT systems in regard to tendencies on transmission performances, emphasizing pressure pulse propagation velocity. The laboratory-scale experiments were conducted at the Institute of Drilling Engineering and Fluid Mining (IBF) from the Technical University Bergakademie Freiberg (TUBAF), namely the Flow-loop Research Facility, to assess the impact of fluid flow rate (and subsequent pressure) on data transmission efficiency. Experimental results demonstrate that increasing the flow rate significantly speeds up signal propagation. In the performed experiments, for the mud siren configuration, increasing the flow rate from 15 to 25 m³/h improved the data transmission performance by approximately, at minimum, 18%, while for the positive mud pulse system, an increase in flow rate from 11.5 to 14 m³/h resulted in a propagation velocity rise of about 19%. The results also showed that higher concentrations of glycerin in the working fluid reduced the propagation velocity, confirming the influence of the fluid’s rheological properties on telemetry performance. At the end, in the presented case study, for 6 bps data rate configurations and for a transmission of a 40-bit string, it was demonstrated that the propagation time from downhole to the surface could potentially represent approximately 40% of the total time demanded for transmitting the desired information (generation plus propagation time). It was verified that an increment of 0.02208 m³/s (350 gpm) could lead to shortening eventual surveying procedures by 1–2 s, and that it could equally represent 1.137 bps. This is a relevant outcome, since, without any physical or functional alteration to the MPT system, one could have the data transmission performance improved, an approach not yet analyzed in the literature nor at the industrial park. These results, added to the detailed literature investigation and interaction with field personnel, indicate that the drilling fluid flow rate is a critical operational parameter affecting both the telemetry signal transmission speed and the overall drilling efficiency. Increasing the flow rate can reduce survey transmission time and decrease operational exposure to drilling hazards, such as drill string sticking. The results provide quantitative information applicable in optimizing measurement-drilling telemetry and help support the development of integrated drilling optimization strategies that balance drilling performance with real-time data transmission assurance in deep drilling operations. Full article

Real-time coal–rock identification is essential for intelligent mining, enabling hazard prevention and geological modeling. However, existing methods often suffer from unclear bit–rock interaction mechanisms, signal distortion, sensor remoteness, or delayed data acquisition, limiting their effectiveness in continuous operations. This study proposes a novel approach for real-time coal–rock identification based on multi-source near-bit drilling data. A near-bit data acquisition system was developed and positioned directly behind the drill bit, integrating sensors to capture high-fidelity parameters—including weight on bit (WOB), torque, rotational speed, rate of penetration (ROP), natural gamma ray, and borehole trajectory—thereby eliminating frictional interference from the drill string. A data-driven theoretical model was established to derive a near-bit drillability index (NDI) for rock strength and to correlate gamma ray responses with lithology. Field trials were conducted in a coal mine in northern Shaanxi, involving over 30 boreholes and systematic core validation. The results demonstrate that the method enables continuous, high-resolution identification of coal–rock interfaces and strength variations along the borehole trajectory, with interpreted results aligning well with core logs and achieving approximately 85% accuracy in strength estimation. By ensuring compatibility with conventional drilling rigs and supporting real-time data transmission and 3D geological updating, this study offers a practical and robust technical pathway for achieving geological transparency and real-time steering in underground coal mining. Full article

Under extreme heterogeneous loading conditions in the deep sea, obtaining well-preserved and stratigraphically coherent cores is a critical challenge that requires urgent resolution. Current methods cannot directly determine the preservation of core stratigraphic information or the sampling behaviour of drill bits through experimentation. Consequently, a new evaluation method for angular velocity-based stratigraphic preservation, which is grounded in Discrete Element Method (DEM) theory, is proposed. Simulation modelling uses the Hertz–Mindlin contact model to construct a multi-scale geotechnical–drill string numerical coupling model. The drill string structure is simplified while incorporating actual geometric dimensions and material properties. By simulating and extracting particle angular velocity data under various operating conditions, a correlation is established between particle motion characteristics and the stratigraphic preservation status. Experiments were conducted on a customised drilling rig platform using specimens with deep-sea geomechanical properties consistent with the simulations. Drilling tools with multiple inner diameter specifications were configured, and multiple variable combinations of the rotational speed and feed rate were set. The degree of bedding preservation in the sampled cores was recorded synchronously. The study clarified the relationship between particle angular velocity and bedding preservation, identifying the influence patterns of parameters such as the tool inner diameter, rotational speed, and feed rate on bedding preservation. Results indicate that when the rotational speed exceeds 200 rpm and the feed rate falls below 0.018 m/s, stratigraphic distortion significantly increases; the drill bit inner diameter exhibits a non-linear negative correlation with core disturbance. This study provides theoretical underpinnings and experimental evidence for multi-parameter process optimisation in maintaining stratigraphic integrity during deep-sea submersible coring operations. Full article

This paper presents a simulation-based artificial neural network (ANN) model to predict bit-rock interaction forces during drilling. Drill string vibration poses a significant challenge in the oil, gas, and geothermal industries, leading to non-productive time and substantial financial losses. This research addresses the challenge of modelling bit-rock interaction excitation forces, which is crucial for predicting vibration and component fatigue life. For a PDC bit with multiple cutters, the cutter tangential velocities at various drilling speeds are calculated, and individual cutter forces are predicted with a two-dimensional discrete element method simulation in which a single cutter moves in a straight line through rock modelled as bonded particles. This data is then used to train an ANN model that characterizes the bit-rock force time series in terms of frequency, amplitude, and distribution of force peaks. Once inserted into a dynamic simulation of the drill string, the algorithm reconstructs the expected bit-rock force time series. A case study using a rigid segment axial and torsional drill string model was used to show that the bit-rock model outputs lead to the expected bit-bounce and stick-slip under certain drilling conditions. Next, the model was implemented in a 3D deviated well drill string simulation with non-linear friction and contact, generating complex stress states with good computational efficiency. Full article

This paper presents a comprehensive study of torsional stick–slip vibrations in rotary drilling systems through a comparison between two lumped parameter models with differing complexity: a simple two-degree-of-freedom (2-DOF) model and a complex high-degree-of-freedom (high-DOF) model. The two models are developed under identical boundary conditions and consider an identical nonlinear friction torque dynamic involving the Stribeck effect and dry friction phenomena. The high-DOF model is calculated with the Finite Element Method (FEM) to enable accurate simulation of the dynamic behavior of the drill string and accurate representation of wave propagation, energy build-up, and torque response. Field data obtained from an Algerian oil well with Measurement While Drilling (MWD) equipment are used to guide modeling and determine simulations. According to the findings, the FEM-based high-DOF model demonstrates better performance in simulating basic stick–slip dynamics, such as drill bit velocity oscillation, nonlinear friction torque formation, and transient bit-to-surface contacts. On the other hand, the 2-DOF model is not able to represent these effects accurately and can lead to inappropriate control actions and mitigation of vibration severity. This study highlights the importance of robust model fidelity in building reliable real-time rotary drilling control systems. From the performance difference measurement between low-resolution and high-resolution models, the findings offer valuable insights to optimize drilling efficiency further, minimize non-productive time (NPT), and improve the rate of penetration (ROP). This contribution points to the need for using high-fidelity models, such as FEM-based models, in facilitating smart and adaptive well control strategies in modern petroleum drilling engineering. Full article

Commitment schemes (CSs) are essential to many cryptographic protocols and schemes with applications that include privacy-preserving computation on data, privacy-preserving authentication, and, in particular, oblivious transfer protocols. For quantum oblivious transfer (qOT) protocols, unconditionally binding commitment schemes that do not rely on hardness assumptions from structured mathematical problems are required. These additional constraints severely limit the choice of commitment schemes to random oracle-based constructions or Naor’s bit commitment scheme. As these protocols commit to individual bits, the use of such commitment schemes comes at a high bandwidth and computational cost. In this work, we investigate improvements to the efficiency of commitment schemes used in qOT protocols and propose an extension of Naor’s commitment scheme requiring the existence of one-way functions (OWFs) to reduce communication complexity for 2-bit strings. Additionally, we provide an interactive string commitment scheme with preprocessing to enable the fast and efficient computation of commitments. Full article

In this paper, we proposed the development of stackable 3D ferroelectric random-access memory (FeRAM), with two select transistors and n capacitors (2TnC), to address scaling limitations for bit density growth and the complicated manufacturing of 3D dynamic random-access memory (DRAM). The proposed 3D FeRAM has a 3D NAND-like architecture, with stacked metal–ferroelectric–metal (MFM) capacitors serving as memory cells in a unit string. A similar manufacturing process is used to achieve a cost-effective process and high bit density for next-generation DRAM applications. The two access transistors, string–select–line (SSL) and ground–select–line (GSL), are perfect string selections. We confirmed that the grounded back gate (GBG) of the proposed architecture can significantly improve the worst disturbance case compared to a floating back gate (FBG) like the 1TnC structure. Also, we confirmed the feasibility of performing the random-access operation during the read operation regardless of the data pattern of the selected string. Full article

This study investigates the geological and geomechanical characteristics of the MIP 1S geothermal well in the Appalachian Basin to optimize drilling and address the wellbore stability issues encountered. Data from well logs, sidewall core analysis, and injection tests were used to derive elastic and rock strength properties, as well as stress and pore pressure profiles. A robust 1D-geomechanical model was developed and validated, correlating strongly with wellbore instability observations. This revealed significant wellbore breakout, widening the diameter from 12 ¼ inches to over 16 inches. Advanced technologies like Cerebro Force™ In-Bit Sensing were used to monitor drilling performance with high accuracy. This technology tracks critical metrics such as bit acceleration, vibration in the x, y, and z directions, Gyro RPM, stick-slip indicators, and bending on the bit. Cerebro Force™ readings identified hole drag caused by poor hole conditions, including friction between the drill string and wellbore walls and the presence of cuttings or debris. This led to higher torque and weight on bit (WOB) readings at the surface compared to downhole measurements, affecting drilling efficiency and wellbore stability. Optimal drilling parameters for future deep geothermal wells were determined based on these findings. Full article

Optimization of drilling processes for oil and gas and geothermal wells requires the effective use of mechanical energy for the destruction of rocks. When constructing a well, an important indicator of the drilling stage is the mechanical speed. Therefore, when performing drilling operations, operators usually use blade bits of an aggressive design and often use forced drilling modes. Drill bits under forced operation modes generate a wide range of vibrations in the drilling tools; in turn, a drill string, being a long-dimensional deformable body, causes the development, amplification, and interconnection of vibrations of different types. Vibration loads reduce the technical and economic indicators of drilling, with destructive effects on drill string elements, and cause complications and emergencies. The authors initiated the creation of an informational and analytical database on emergency situations that occurred as a result of excessive vibrations of the drill string during the construction of deep wells in the deposits of the Dnipro–Donetsk Basin. For the first time, the suitability and effectiveness of using the Smart 4 controller (“Innova Power Solutions”, Calgary, Canada) for monitoring the vibration load of the drilling tool was tested in industrial conditions, while the controller was used as a separate element in the drill string. A special module was developed for the reliable installation of the Smart 4 controller, with a power battery in the layout of the lower part of the drill string. During the testing of the proposed device for measuring vibrations in the process of drilling an inclined well, verification of the registered data was carried out with the help of a high-cost telemetry system. The implementation of the proposed innovation will allow each operator to assess the significance of the impact of vibrations and shocks on the production process and, if necessary, adjust the drilling modes or apply vibration protection devices. In addition, service departments that operate and repair drilling equipment will be able to obtain an evidence base for resolving warranty disputes or claims. Full article

One of the industries with the fastest rate of growth is healthcare, and this industry’s enormous amount of data requires extensive cloud storage. The cloud may offer some protection, but there is no assurance that data owners can rely on it for refuge and privacy amenities. Therefore, it is essential to offer security and privacy protection. However, maintaining privacy and security in an untrusted green cloud environment is difficult, so the data owner should have complete data control. A new work, SecPri-BGMPOP (Security and Privacy of BoostGraph Convolutional Network-Pinpointing-Optimization Performance), is suggested that can offer a solution that involves several different steps in order to handle the numerous problems relating to security and protecting privacy. The Boost Graph Convolutional Network Clustering (BGCNC) algorithm, which reduces computational complexity in terms of time and memory measurements, was first applied to the input dataset to begin the clustering process. Second, it was enlarged by employing a piece of the magnifying bit string to generate a safe key; pinpointing-based encryption avoids amplifying leakage even if a rival or attacker decrypts the key or asymmetric encryption. Finally, to determine the accuracy of the method, an optimal key was created using a meta-heuristic algorithmic framework called Hybrid Fragment Horde Bland Lobo Optimisation (HFHBLO). Our proposed method is currently kept in a cloud environment, allowing analytics users to utilise it without risking their privacy or security. Full article

Martian rocks contain crucial information about the genesis of Mars and the historical evolution of Martian climate change. Consequently, extracting and examining Martian rocks are pivotal in advancing our comprehensive understanding of the red planet. However, the current core drill string is prone to wear and tear, and the samples are susceptible to thermal denaturation. To address these challenges, we introduce two novel types of drill bits, the conical straight junk slot and the conical spiral junk slot, both employing impregnated diamond as the primary material. Comparative experiments were meticulously conducted to evaluate the influence of different junk configurations on drilling parameters, including speed, abrasion resistance, drilling force loading, and sample temperature rise. The findings unequivocally demonstrate the superior performance of the spiral junk slot. Furthermore, simulations were performed to examine the drilling process on basalt using a fixed configuration drill bit, validating the occurrence of the sample temperature rise. The research presented in this paper offers valuable programmatic references and essential data support for future Martian rock coring drilling missions. Full article

Until early 2006, in Brazil, the focus used to be on oil and gas exploration/exploitation of post-salt carbonates. This changed when the industry announced the existence of large fields in pre-salt layers across the South Atlantic Ocean from nearshore zones up to almost 350 [km] from the shore. With the discovery of pre-salt hydrocarbons reservoirs, new challenges appeared. One of the main challenges is the necessity to optimize the drilling processes due to their high operational costs. Drilling costs are considerably high, which leads the oil and gas industry to search for innovative and entrepreneurial methods. The coupling of the mechanical specific energy (MSE) and the rate of penetration (ROP) is a method that allows for the identification of ideal conditions to efficiently enhance the drilling process. In addition, the performance of the drilling process can be estimated through pre-operational tests, which consist in continuously testing the applied drilling mechanic parameters, such as the weight-on-bit (WOB) and drill string rotary speed (RPM), looking for optimum sets that would ultimately provide the most desirable ROP. Thus, the goal of this research was to analyze field data from pre-salt layer operations, using a multi-objective optimization based on the play-back methodology for pre-operational drilling tests, through the ideal combination of the highest ROP and the lowest MSE. The results showed that the new concept of pre-operational tests based on the MSE proved to be effective in the drilling process optimization. The combination of the highest ROP and the lowest MSE allows for a high-performance drilling process. For WOB intervals of 5 and 7 [klb], a good fit of the parameters was obtained. Through the parameters obtained from pre-operational tests, the eventual cost-saving and time-saving values could be estimated, respectively, ranging from USD 1,056,180 to 1,151,898 and 19.50 to 21.27 [h], respectively. In addition, the results of this research can be applied to the exploration of other natural resources, such as natural hydrogen and geothermal sources. Full article

Fully homomorphic encryption (FHE) cryptographic systems enable limitless computations over encrypted data, providing solutions to many of today’s data security problems. While effective FHE platforms can address modern data security concerns in unsecure environments, the extended execution time for these platforms hinders their broader application. This project aims to enhance FHE systems through an efficient parallel framework, specifically building upon the existing torus FHE (TFHE) system chillotti2016faster. The TFHE system was chosen for its superior bootstrapping computations and precise results for countless Boolean gate evaluations, such as AND and XOR. Our first approach was to expand upon the gate operations within the current system, shifting towards algebraic circuits, and using graphics processing units (GPUs) to manage cryptographic operations in parallel. Then, we implemented this GPU-parallel FHE framework into a needed genomic data operation, specifically string search. We utilized popular string distance metrics (hamming distance, edit distance, set maximal matches) to ascertain the disparities between multiple genomic sequences in a secure context with all data and operations occurring under encryption. Our experimental data revealed that our GPU implementation vastly outperforms the former method, providing a 20-fold speedup for any 32-bit Boolean operation and a 14.5-fold increase for multiplications.This paper introduces unique enhancements to existing FHE cryptographic systems using GPUs and additional algorithms to quicken fundamental computations. Looking ahead, the presented framework can be further developed to accommodate more complex, real-world applications. Full article