Search Results (161)

Downhole kick is one of the most severe safety hazards in deep and ultra-deep well drilling operations. Traditional monitoring methods, which rely on surface flow rate and fluid level changes, are limited by their delayed response and insufficient sensitivity, making them inadequate for early warning. This study proposes a real-time monitoring technique for gas content in drilling fluid based on the attenuation principle of Ba-133 γ-rays. By integrating laboratory static/dynamic experiments and Geant4-11.2 Monte Carlo simulations, the influence mechanism of gas–liquid two-phase media on γ-ray transmission characteristics is systematically elucidated. Firstly, through a comparative analysis of radioactive source parameters such as Am-241 and Cs-137, Ba-133 (main peak at 356 keV, half-life of 10.6 years) is identified as the optimal downhole nuclear measurement source based on a comparative analysis of penetration capability, detection efficiency, and regulatory compliance. Compared to alternative sources, Ba-133 provides an optimal energy range for detecting drilling fluid density variations, while also meeting exemption activity limits (1 × 10⁶ Bq) for field deployment. Subsequently, an experimental setup with drilling fluids of varying densities (1.2–1.8 g/cm³) is constructed to quantify the inverse square attenuation relationship between source-to-detector distance and counting rate, and to acquire counting data over the full gas content range (0–100%). The Monte Carlo simulation results exhibit a mean relative error of 5.01% compared to the experimental data, validating the physical correctness of the model. On this basis, a nonlinear inversion model coupling a first-order density term with a cubic gas content term is proposed, achieving a mean absolute percentage error of 2.3% across the full range and R² = 0.999. Geant4-based simulation validation demonstrates that this technique can achieve a measurement accuracy of ±2.5% for gas content within the range of 0–100% (at a 95% confidence interval). The anticipated field accuracy of ±5% is estimated by accounting for additional uncertainties due to temperature effects, vibration, and mud composition variations under downhole conditions, significantly outperforming current surface monitoring methods. This enables the high-frequency, high-precision early detection of kick events during the shut-in period. The present study provides both theoretical and technical support for the engineering application of nuclear measurement techniques in well control safety. Full article

Ultra-high-temperature and pressure downhole environments pose challenges for conventional electronic instruments to adapt to high-temperature formations, thereby restricting the application of downhole electronic tool technology in deep and ultra-deep wells. Given the aforementioned limitation of electronic inclination measurement systems, specifically their poor temperature resistance, this study proposes a novel shunt flow control method. This method employs a mechanical structure to overcome temperature constraints: gravitational torque generated by the mechanical structure is utilized to control valve opening and regulate flow rate. By converting sensed well inclination information into changes in flow rate, this approach enables the transformation of well inclination sensing and its associated signals. In this study, a kinetic analysis model of the shunt-regulating valve spool was established. Using computational fluid dynamics (CFD) simulations, the flow characteristics of the regulating spool were analyzed under varying valve openings. The structure of the flow control valve was optimized with the goal of maximizing internal flow. Finally, the reliability of the designed structure for well deviation sensing and flow control was verified using simulation experimental studies and theoretical analyses. Full article

In the drilling process of ultra-deep wells with large-diameter boreholes, the transport and deposition behavior of cuttings plays a critical role in maintaining wellbore cleanliness and ensuring operational safety. Due to the geometry of enlarged boreholes and their complex annular flow characteristics, conventional single-parameter control methods often fail to achieve effective cuttings transport. This study aims to identify the dominant influencing factors and optimize key parameters by focusing on the cuttings volume fraction as a primary evaluation metric. A numerical simulation approach is employed to systematically investigate the influence of stabilizer geometry and hydraulic parameters. Five variables—drilling fluid velocity, drill pipe rotational speed, number of stabilizers, flow area, and helical angle—are selected for analysis. An initial one-factor sensitivity analysis is conducted to evaluate local impacts and to establish relative sensitivity indices, thereby identifying key variables. A variance-based global sensitivity analysis is further applied to quantify first-order effects, full-order effects, and interaction contributions, revealing nonlinear coupling and synergistic mechanisms. The results indicate that drilling fluid velocity and rotation speed exhibit the most significant first-order influences, while stabilizer-related parameters show strong interaction effects that are often underestimated by traditional methods. Based on these findings, an optimized cuttings transport scheme for large-diameter boreholes is proposed. Additionally, a multi-parameter response model for the cuttings volume fraction is developed using sensitivity-weighted analysis, offering theoretical support and methodological reference for enhancing cuttings transport performance and structural design in large-diameter borehole drilling operations. Full article

The accurate prediction of static formation temperature (SFT) is essential for ensuring safety and efficiency in ultra-deep well drilling operations. Excessive downhole temperatures (>150 °C) can degrade drilling fluids, damage temperature-sensitive tools, and pose serious operational risks. Conventional methods for SFT determination—including direct measurement, temperature recovery inversion, and artificial intelligence models—are often limited by post-drilling data dependency, insufficient spatial resolution, high computational costs, or a lack of adaptability to complex wellbore geometries. In this study, we propose a new pseudo-3D Kriging interpolation framework that explicitly incorporates real wellbore trajectories to improve the spatial accuracy and applicability of pre-drilling SFT predictions. By systematically optimizing key hyperparameters (θ = [10, 10], lob = [0.1, 0.1], upb = [20, 200]) and applying a grid resolution of 100 × 100, the model demonstrates high predictive fidelity. Validation using over 5.1 million temperature data points from 113 wells in the Shunbei Oilfield reveals a relative error consistently below 5% and spatial interpolation deviations within 5 °C. The proposed approach enables high-resolution, trajectory-integrated SFT forecasting before drilling with practical computational requirements, thereby supporting proactive thermal risk mitigation and significantly enhancing operational decision-making on ultra-deep wells. Full article

Creep and stress sensitivity can lead to the long-term conductivity degradation of fractures, and this influences the accuracy of long-term productivity predictions in ultra-deep carbonate reservoirs (UDCRs). However, the current models do not consider these two factors. For the long-term conductivity degradation of acid-etched symmetry fractures in UDCRs, a new fracture permeability evolution model incorporating creep and stress sensitivity effects was established. Building upon this, a numerical simulation model for UDCRs was developed for the first time to quantitatively analyze the impacts of creep, stress sensitivity, and production strategies on well productivity. The research revealed that the creep and stress sensitivity characteristics of acid-etched fractures had a significant impact on the well productivity for UDCRs. The larger the creep coefficient and stress sensitivity coefficient, the lower the oil well productivity. The larger the initial reservoir pressure and drawdown pressure, the higher the daily production and cumulative production of the oil well, but the cumulative production growth rate decreased. The cumulative production in the early stage of the released-pressure production was significantly higher than that of the pressure-controlled production, but with the increase in the pressure-controlled time, the cumulative production reversed. When the pressure was controlled for three years, the cumulative production increased by 5952 m³ (38.8%); as the creep coefficient increased, the cumulative production increased by greater than the pressure-released production. This shows that the larger the creep coefficient, the better the effect of controlling pressure production. The research results can provide a theoretical basis and technical support for the efficient development of UDCRs. Full article

With the expansion of oil and gas exploration and development to complex oil and gas resource areas such as deep and ultra-deep formation onshore and offshore, the kick is one of the high drilling risks, and timely and accurate early kick detection is increasingly important. Based on the kick generation mechanism, kick characterization parameters are preliminarily selected. According to the characteristics of the data and previous research progress, Random Forest (RF), Support Vector Machine (SVM), Feedforward Neural Network (FNN), and Long Short-term Memory Neural Network (LSTM) are established using experimental data from Memorial University of Newfoundland. The test results show that the accuracy of the SVM-linear model was 0.968, and the missing alarm and the false alarm rate only was 0.06 and 0.11. Additionally, through the analysis of the kick response time, the lag time of the SVM-linear model was 1.3 s, and the comprehensive equivalent time was 23.13 s, which showed the best performance. The different effects of the model after data transformation are analyzed, the mechanism of the best effect of the SVM model is analyzed, and the changes in the effect of other models including RF are further revealed. The proposed early-warning model warns in advance in historical well logging data, which is expected to provide a fast, efficient, and accurate gas kick warning model for drilling sites. Full article

Background/Objectives: Skeletal dysplasias are a heterogeneous group of rare genetic disorders with diverse and overlapping clinical presentations, posing diagnostic challenges even for experienced clinicians. With the increasing availability of artificial intelligence (AI) in healthcare, large language models (LLMs) offer a novel opportunity to assist in rare disease diagnostics. This study aimed to compare the diagnostic accuracy of two advanced LLMs, ChatGPT (version GPT-4) and DeepSeek, with that of a clinical expert panel in a cohort of pediatric patients with genetically confirmed skeletal dysplasias. Methods: We designed a prospective vignette-based diagnostic benchmarking study including 45 children with confirmed skeletal dysplasias from two tertiary centers. Both LLMs were prompted to provide primary and differential diagnoses based on standardized clinical case vignettes. Their outputs were compared with those of two human experts (a pediatric endocrinologist and a pediatric orthopedic surgeon), using molecular diagnosis as the gold standard. Results: ChatGPT and DeepSeek achieved a comparable diagnostic top-3 accuracy (62.2% and 64.4%, respectively), with a high intermodel agreement (Cohen’s κ = 0.95). The expert panel outperformed both models (82.2%). While LLMs performed well on more common disorders, they struggled with ultra-rare and multisystemic conditions. In one complex case missed by experts, the DeepSeek model successfully proposed the correct diagnosis. Conclusions: LLMs offer a complementary diagnostic value in skeletal dysplasias, especially in under-resourced medical settings. Their integration as a supportive tool in multidisciplinary diagnostic workflows may enhance early recognition and reduce diagnostic delays in rare disease care. Full article

During the drilling processes of a 10,000-meter-deep well, cutting removal becomes difficult in the 32-inch borehole, which significantly increases downhole risks and affects drilling efficiency. To address this, a numerical simulation method based on the Eulerian two-fluid model was established for cuttings transport simulation in ultra-large boreholes. This method revealed the cuttings transport behavior in the 32-inch borehole of the SDCK1 well, analyzed the actual return velocity and the critical return velocity required for cuttings transport, and examined the cuttings transport characteristics near the bottom stabilizer. The results show that under the maximum flow rate of 160 L/s, the actual return velocity in the annulus is only 0.32 m/s, while the critical return velocity for 10 mm cutting particles is 0.57 m/s. Except for the stabilizer position, the actual return velocity throughout the entire well section is lower than the critical return velocity required for 10 mm cutting particles transport, which is one of the main reasons for the poor cutting removal in the wellbore. Near the bottom stabilizer, the annular flow is altered by the large outer diameter of the stabilizer, causing drilling fluid backflow and resulting in cuttings accumulation. The cuttings backflow and accumulation are more pronounced with the double stabilizer tool combination compared to the triple stabilizer tool combination. The small annular gap near the stabilizers makes it difficult for large cuttings to pass through, leading to blockages. A low annular return velocity and cuttings accumulation near the stabilizer are the primary reasons for poor cuttings removal in the 32-inch borehole. Full article

To address the challenge of ultra-deep desulfurization in fuels, a series of heteropolyacid-based poly(ionic liquid) catalysts (C4-PIL@PW, C8-PIL@PW, and C16-PIL@PW) were synthesized via radical polymerization and anion exchange methods. The prepared catalysts were characterized via FT-IR, XRD pattern, and Raman spectroscopy. Optimal reaction parameters (e.g., temperature, catalyst dosage, and O/S molar ratio) were systematically investigated, as well as the catalytic mechanism. The typical sample C8-PIL@PW exhibited exceptional oxidative desulfurization (ODS) performance, achieving a sulfur removal of 99.2% for dibenzothiophene (DBT) without any organic solvent as extractant. Remarkably, the sulfur removal could still retain 89% after recycling five times without regeneration. This study provides a sustainable and high-efficiency catalyst for ODS, offering insights into fuel purification strategies. Full article

Look-ahead electromagnetic (EM) logging-while-drilling (LWD) plays an indispensable role in the prediction of deep and ultra-deep reservoirs. Traditional electromagnetic logging-while-drilling (EMLWD) and ultra-deep EMLWD technologies exhibit certain limitations in the real-time detection of ahead-of-bit formations, making it challenging to meet precision drilling requirements under complex well conditions, with the development of petroleum and gas geology and exploration progress I n the direction of deep, ultra-deep, and complex reservoirs. As a new LWD technology, look-ahead EMLWD enables real-time identification of formation structures, fluid distributions, and interface positions ahead of the drill bit during the drilling process by leveraging the propagation characteristics of EM. This capability provides critical decision-making support for wellbore trajectory optimization, drilling risk assessment, and reservoir evaluation. Therefore, this paper conducts research on theoretical methodologies for look-ahead EMLWD. Leveraging the Born geometric factor theory, we derive the expression for the 3D geometric factor spatial signal and analyze the sensitivity of each component related to look-ahead. Building on this foundation, we establish the sensitivity expression for look-ahead operations and investigate the impact of various antenna configurations on its signal. The results indicate that the coaxial component (gzz) and coplanar components (gxx and gyy) are the primary contributors to look-ahead EMLWD. As frequency decreases and spacing increases, the sensitive region for look-ahead expands. Moreover, look-ahead detection sensitivity becomes increasingly concentrated in front of the drill bit, while the signal at the opposite end is attenuated by incorporating additional coils. Under identical formation conditions, compared with a single-transmitter single-receiver system, a single-transmitter double-receiver coil system exhibits a significantly stronger signal amplitude and more pronounced changes at the formation boundary. Additionally, this configuration enhances sensitivity and extends the sensitive distance in response to variations in formation resistivity. Full article

The identification and prediction of effective reservoir rocks are important for evaluating the energy production potential of ultra-deep tight sandstone reservoirs. Taking the Keshen gas field, Tarim Basin, as an example, three distinct petrofacies are divided according to petrology, pores, and diagenesis. Petrofacies, well logs, and factor analysis are combined to predict effective reservoir rocks. We find that petrofacies A has a relatively coarse grain size, moderate mechanical compaction, diverse but low-abundance authigenic minerals, and well-developed primary and secondary pores. It is an effective reservoir rock. Petrofacies B and petrofacies C are tight sandstones with a poorly developed pore system and almost no dissolution. Petrofacies B features abundant compaction-susceptible ductile grains, intense mechanical compaction, and underdeveloped authigenic minerals, while petrofacies C features pervasive carbonate cementation with a poikilotopic texture. We combine well logging with gamma ray, acoustic, bulk density, neutron porosity, resistivity, and factor analyses to facilitate the development of petrofacies prediction models. The models reveal interbedded architecture where effective reservoir rocks are interbedded with tight sandstone, resulting in the restricted connectivity and pronounced reservoir heterogeneity. Classifying and combining well logs with a factor analysis to predict petrofacies provide an effective means for evaluating the energy potential of ultra-deep reservoirs. Full article

Compared with traditional gas reservoirs, ultra-deep and ultra-high-pressure tight sandstone gas reservoirs are characterized by well-developed faults and fractures, strong heterogeneity and stress sensitivity, and complex in situ stress distribution. Traditional three-dimensional geological models and numerical models ignore the variation characteristics of reservoir in situ stress during the production process, it affects the accuracy of the subsequent fracturing modification design and development plan formulation. Therefore, based on the integrated method of geological engineering, this article first carried out high-temperature and high-pressure stress sensitivity tests on reservoir rock samples and fitted the stress-sensitive mathematical model to clarify the influence of high temperature and high pressure on permeability. Then, aiming at the problem of four-dimensional in situ stress variation caused by the coupling of the seepage field and stress field during the exploitation of tight sandstone gas reservoirs, combined with the results of well logging interpretation, rock physical property analysis, and mechanical experiments, based on the three-dimensional geological model and geomechanical model of the gas reservoir and coupled with the stress-sensitive characteristics of the reservoir, a four-dimensional in situ stress model for the reservoir of tight sandstone gas reservoirs was established. The prediction of the variation law of four-dimensional in situ stress during the production process was carried out. Finally, the influence of considering stress sensitivity on reservoir production was simulated. The results show the following: ① The production process has a significant impact on the magnitude and distribution of four-dimensional in situ stress. With the decrease in pore pressure, both the maximum horizontal principal stress and the minimum horizontal principal stress decrease. ② In the area near the production well, the direction of in situ stress will significantly deflect over time. ③ In an ultra-deep and ultra-high-pressure environment, the gas reservoir is affected by the stress-sensitive effect. The stable production time of the gas well is reduced by two years, and the cumulative gas production decreases by 5.01 × 10⁸ m³. The research results provide the temporal stress field distribution results for the simulation and prediction of the secondary fracturing of old wells and the commissioning fracturing of new wells in the target well area. Full article

The pore structure of shale is a critical factor influencing the occurrence and flow of shale gas. Characterizing the pore structure and studying its heterogeneity are of paramount importance for a deeper understanding of the laws governing hydrocarbon occurrence, as well as for enhancing the efficiency of exploration and development. This work addresses the complex characteristics of multiscale coupling in the pore systems of shale reservoirs, focusing on the ultra-deep Qiongzhusi Formation shale in the southern region. Through the integrated application of cross-scale observation techniques and physicochemical analysis methods, a refined analysis of the pore structure is achieved. Utilizing field emission scanning electron microscopy imaging technology, the types and morphological characteristics of pores are identified. Additionally, a fluid–solid coupling analysis method employing high-pressure mercury intrusion and low-temperature gas adsorption (CO₂/N₂) is utilized to elucidate the characteristics of pore structure and heterogeneity while also analyzing the influence of matrix components on these features. The results indicate that the shale of the Qiongzhusi Formation is rich in feldspar minerals, facilitating the development of numerous dissolution pores, with the pore system predominantly consisting of inorganic mineral pores. The full pore size curve of the shale generally exhibits a bimodal characteristic, with a high proportion of mesopores. A strong positive linear relationship is observed between pore volume and specific surface area, whereby larger pore spaces reduce pore heterogeneity, with mesopore volume playing a decisive role. This study provides scientific support for the evaluation and strategic deployment of exploration and development in ultra-deep shale reservoirs of the Qiongzhusi Formation. Full article

A study was conducted on the mechanical behavi or of the completion string in a 10,000 m ultra-deep well from western China’s oilfields to identify the causes of plastic failure in the string. This article analyzes the interaction between fluid and tubing in high-pressure and high-production gas wells by establishing a fluid structure coupling four-equation model. Through fatigue tests, it was found that P110 tubing material has a stress amplitude related ratchet effect, revealing the softening characteristics of tubing material. Through case analysis, the fatigue of the entire wellbore was analyzed, and it was shown that the fatigue hotspot is concentrated near the neutralization point, and stress concentration under high-production and low-production conditions leads to the degradation of tubing material performance under fatigue load. After continuous service for 30 days under high-production and low-production conditions, the entire wellbore section exhibited a softening phenomenon, and the yield strength began to decrease below 4349 m and 4324 m well depths, respectively. The safety factor of the entire wellbore section decreased. Within 284 days of production, the fatigue damage of the entire wellbore section was less than 5%, and the remaining yield change and material softening of the tubing string were negligible. However, there was an impact load during the lifecycle, which caused severe fluctuations in the wellbore safety factor and was the main cause of tubing string fracture. Subsequent research should integrate diverse well cases exhibiting varying production parameters to establish a statistically robust predictive framework for safety factor variations. Full article

This paper presents the world’s first radar detection experiment conducted in a 7500-m ultra-deep well. By applying ground-penetrating radar technology to petroleum logging, the developed borehole radar system successfully achieved stratigraphic information detection in the 7200–7500 m section of Shunbei Well No. 2. Utilizing electromagnetic wave reflection principles, the system acquires echo signals carrying medium characteristics through transmit–receive antenna arrays coupled with field-programmable gate array (FPGA)-based high-speed acquisition for real-time downhole data transmission. Experimental results demonstrate high consistency in Gamma Ray (GR) curves (correlation coefficient: 0.92) between radar data and Sinopec’s geological drilling data, particularly in key stratigraphic features such as casing reflections at a 7250-m depth (error of 0.013%). This breakthrough validates the operational stability and detection accuracy of borehole radar in complex subsurface environments, providing an innovative technological approach for ultra-deep hydrocarbon exploration. Full article