Oil and Gas Center

Fire-flooding, a mainstream thermal recovery technology for heavy oil reservoirs, requires large-scale continuous air injection and inevitably generates substantial fire-flooding tail gas with a high greenhouse gas content, posing a severe challenge to the environmental sustainability of offshore oil exploitation. To address this critical issue and realize carbon-neutral development, this study proposes an integrated near-zero emission framework for offshore heavy oil fire-flooding tail gas based on multipath storage combined with intelligent optimization algorithms, addressing the limitations of single storage methods and insufficient intelligent integration in existing research. The framework integrates fire-flooding tail gas capture, transportation, and reinjection into adjacent light oil and hydrate-bearing reservoirs to synergistically achieve carbon storage and enhanced oil recovery (EOR), with a multiobjective optimization system established via BP neural networks and optimization algorithms (genetic algorithm and particle swarm optimization) to efficiently optimize injection-production parameters. Key results show that all involved reservoirs exhibit three distinct production stages, and the optimal tail gas reinjection timing is within the first 1000 days of fire-flooding. The proposed emission mode and optimization method achieve the dual goals of near-zero carbon emission and production enhancement, verifying the feasibility and superiority of the multipath utilization scheme and providing important theoretical guidance and technical support for the efficient, low-carbon, and sustainable development of offshore heavy oil resources.

Mechanical characterization of shales is a fundamental requirement in optimizing shale resource development and transferring development strategies between shale plays. In the Indonesian context, where presently limited subsurface data exist, such mechanical insights are essential for evaluating the viability of organic-rich shales as potential hydrocarbon resource. Here we report laboratory-based mechanical properties of several Indonesian organic-rich shales with hydrocarbon potential located within Tertiary basins in an active margin settings. Samples from surface-outcrops of lacustrine sediments in the Central Sumatra Basin (CSB) and subsurface-cores of marine deposits in the North Sumatra Basin (NSB) were examined in a series of experiments for their mechanical properties, including rock strength, elastic properties, and creep compliance. Results show that the Indonesian shales studied here are generally more compliant than Mesozoic/Paleozoic U.S. shales reported in the literature. Within the context of a binary mixture model of stiff and soft components used to explain shale elastic properties, these differences in mechanical properties imply that the soft and stiff end-members are more compliant in Indonesian shales than in U.S. shales. We interpret these differences as the difference in mechanical maturity, which reflects the degree to which mechanical properties have evolved over time due stress-driven diagenesis. CSB and NSB samples are early mature, mechanically, compared to the mechanically mature U.S. shales because of their younger age and limited time for stress-driven compaction to take place. Particularly, the Baong Formation samples from the NSB studied here come from a hard-overpressured interval and are mechanically immature, despite their moderate thermal maturity, because of their exposure to lower effective stress. Laboratory results also show no significant differences in mechanical properties between shales deposited in lacustrine (CSB samples) and marine (NSB samples) environments. Our interpretation provides a reason for why brittleness could vary between shale rocks even when mineral composition and thermal maturity are similar, and emphasizes the importance of geological age in determining the mechanical properties of organic-rich shales.

This study investigates the protective performance of a triazole-based Mannich base corrosion inhibitor, 4-((1,2,4-triazolyl)methyl) dibutylamine (TZMBA), on P110 carbon steel in dissolved oxygen environments. TZMBA was synthesized via a Mannich reaction, and its molecular structure was confirmed by Fourier transform infrared spectroscopy (FT-IR). The corrosion inhibition behavior and underlying mechanisms were systematically explored through weight loss measurements, surface characterization, and multiscale molecular simulations. Weight loss results indicated that TZMBA significantly mitigates the corrosion of P110 steel, with inhibition efficiency reaching 81.5% at 1.67 mmol/L and 82.0% at 2.14 mmol/L. Adsorption thermodynamic analysis revealed that the process follows the Langmuir isotherm model. The calculated standard Gibbs free energy ∆Gads0 of −38.69 kJ/mol suggests a spontaneous, mixed-type adsorption mechanism involving both physisorption and chemisorption. Scanning electron microscopy (SEM) observations confirmed a marked reduction in surface degradation, characterized by suppressed corrosion products and minimized localized attack. X-ray photoelectron spectroscopy (XPS) further verified that TZMBA anchors to the metal surface through chemical coordination, forming a robust organic-inorganic composite film. From a theoretical perspective, frontier molecular orbital (FMO) analysis showed that TZMBA’s high EHOMO and narrow energy gap facilitate efficient electron transfer. Combined Fukui function and molecular electrostatic potential (MEP) maps identified the nitrogen atoms in the triazole ring and amine group as the primary active sites. Furthermore, molecular dynamics (MD) simulations demonstrated that TZMBA molecules adopt a nearly parallel configuration on the Fe surface. The high negative interaction energy obtained from MD simulations confirms a strong binding affinity and a potent inherent driving force for the formation of a stable protective layer. Overall, the integration of experimental data and theoretical calculations establishes TZMBA as an effective inhibitor that provides superior protection by forming a stable, compact adsorption film on P110 carbon steel.

Summary Gas drilling is a promising technique for developing tight sandstone reservoirs. Cuttings accumulation in horizontal and deviated gas drilling impairs wellbore cleaning, reducing drilling efficiency and elevating operational risks. A novel model for predicting cuttings bed height in horizontal and deviated gas drilling is proposed. Based on particle dynamics theory, mechanical equilibrium equations are derived for three distinct cuttings initiation mechanisms—sliding, rolling, and lifting—to solve for the critical frictional velocity. Combined with wellbore geometric relationships, the cuttings bed height is predicted using an iterative method. This model is validated by computing the critical annular gas velocity and comparing the results with previous experimental data, yielding average prediction errors of 12.1% and 11.1%. Based on the model, the effects of key parameters, including wellbore inclination, equivalent particle diameter, particle sphericity, exposure level, and gas injection rate, on cuttings bed height are analyzed. The results indicate that wellbore inclination exerts a threshold effect on cuttings bed height. Specifically, cuttings bed height rises as inclination increases up to the 60–65° range, where the bed height peaks and declines as inclination continues to rise beyond this interval. This trend holds across different equivalent particle diameters. Cuttings initiation mode is also consistent across different equivalent particle diameters, adopting the lifting mode at inclinations below 60° and shifting to the rolling mode at inclinations around 60° and above. Equivalent particle diameter also affects cuttings bed height, with particularly pronounced effects in the range of 1–5 mm. Higher particle sphericity promotes accumulation, while higher exposure level and gas injection rate reduce it. This model provides a reliable tool for optimizing drilling parameters to mitigate cuttings bed accumulation, thereby supporting the efficient development of tight sandstone reservoirs.

Natural gas transmission networks require rapid operational decisions that integrate geographic information systems data, network topology, and time indexed measurements from operational systems. While large language models can reduce the interaction barrier for engineers, text only generation is unreliable for safety critical computations and rarely provides auditable evidence. This paper presents Pipeline-Agent, a decision support system for natural gas pipelines built on verifiable computational reasoning. Pipeline-Agent aligns heterogeneous sources into a unified spatiotemporal schema, creates an explicit plan, executes only deterministic tools within a sandboxed workspace, and returns a verifiable result package that includes intermediate artifacts and execution logs. We further introduce Pipeline-Bench, a benchmark with eighty task templates spanning eight categories. Across evaluation runs, Pipeline-Agent achieves a 2.24 × higher mean score than the best baseline and a 2.56 × higher mean score than OpenAI GPT-5.2 direct generation. The results indicate that tool grounded agents with explicit planning and verification can provide practical and transparent decision support for pipeline operations.