埃克森美孚

As AI systems increasingly exhibit agentic behavior, discussions of autonomy often conflate what systems are technically capable of doing with what they should be permitted to do in practice. This paper introduces a governance framework that explicitly separates Allowed Autonomy Levels (AAL), which define the degree of autonomy an AI agent is authorized to exercise given risk, oversight, and accountability considerations, from Autonomous Capability Levels (ACL), which characterize an agent's inherent technical abilities. We present a structured set of autonomy levels spanning reactive execution, decision support, supervised action, goal-directed autonomy, and delegated operational authority, and describe how control, reversibility, and accountability change as autonomy increases. To operationalize this framework, we propose a risk-aware decision process for assigning allowed autonomy, analyze how risk and accountability evolve across autonomy levels, and demonstrate its application through a deployed enterprise data engineering agent, illustrating how a system assessed at a high capability level can be deliberately constrained to a lower allowed autonomy based on risk, reversibility, and organizational readiness. By distinguishing authorization from capability, this work provides practical guidance for the design, deployment, and governance of Agentic AI systems.

Abstract During the Liza Phase 1 development of the Guyana deepwater field, conventional Reservoir Drill-In Fluids (RDIF) were employed. However, as well complexity increased, there arose a necessity for a more robust and versatile fluid capable of not only meeting or surpassing these challenges but also accommodating the diverse well types and completion methods slated for subsequent developments. This paper meshes global author experiences with Guyana-specific project experiences and includes some of the findings during laboratory testing conducted to validate the new RDIF used in Guyana and emphasizes the performance enhancements observed in the field. Notable improvements include a significant reduction in plastic viscosity and overall rheological profile, enabling efficient drilling while maintaining Equivalent Circulating Density (ECD) within the narrow Pore Pressure-Fracture Gradient (PPFG) window. Furthermore, the micronized ilmenite minimizes the risk of weighting agent sag issues and allows significant reduction in critical path RDIF filtering time prior to running completion screens compared to API barite systems. A breaker system was used on selected wells to partially dissolve filtercake to increase injectivity on gas-first injectors. Three primary RDIFs were trialed in Guyana during Liza Phase 1 and Phase 2: (1) Non-Aqueous Fluid (NAF) weighted with API Barite, (2) NAF weighted with Ultra Fine Grind (UFG) Barite, and (3) NAF weighted with 100% Calcium Carbonate (CaCO3). Each fluid exhibited varying degrees of success depending on the completion type, but limitations emerged impacting well productivity or injectivity. Key challenges included high ECD nearing the reservoir's Fracture Gradient, posing a heightened risk of lost circulation. Such risk could be mitigated with shorter reservoir intervals, controlled Rate of Penetration (ROP), and reduced tripping speeds. Other complexities called for increased vigilance and dilution to manage fluid properties, increased storage needs, and increased logistics for three distinct RDIF systems. In essence, conventional drill-in fluids had reached their technical limitation. For the second (Liza Phase 2) and third (Payara) developments, the Alliance Partners (Alliance) collaborated to design and implement a new high-performance, non-aqueous RDIF. This fluid, weighted with a specific Particle Size Distribution (PSD) of micronized ilmenite and sized CaCO3, aimed to deliver benefits equivalent to a 100% CaCO3 system with enhanced ECD control and adaptability to all well completion types. Increased well productivity and injectivity were observed with this micronized ilmenite fluid compared to previous systems. This paper presents results from actual wells using RDIF containing micronized ilmenite as the primary weighting agent showing increased productivity and injectivity compared to barite and 100% CaCO3 RDIF systems used in the first field development. Additionally, the innovative RDIF reduced ECD, critical path RDIF filtering time prior to running completion screens, dilution rates, Liquid Mud Plant (LMP) volumes, and proved to be effectively reusable across multiple wells without compromising performance.

This study evaluated airborne laser scanning (ALS) as a large-scale tool for forest carbon quantification by comparing ALS-derived estimates with traditional field sampling across multiple forest strata. Above-ground biomass was estimated using two different, commonly used equations, while below-ground biomass was derived from peer-reviewed root-to-shoot ratios. ALS and field estimates differed across forest strata and carbon pools: ALS detected higher live tree carbon in harvested areas—capturing residual trees often missed in traditional cruises—but underestimated dead wood carbon, relative to field-based methods. Consistent differences were also observed between biomass equations, with Woodall estimates being 12.8% and 16.7% lower than Jenkins estimates for ALS and field methods, respectively. The study further incorporated soil organic carbon (SOC) and carbon dating data, providing additional insight into subsurface carbon stocks and the temporal dynamics of forest carbon pools. Overall, ALS proved to be an efficient, repeatable, and scalable method for carbon assessment, offering clear advantages in monitoring carbon flux over time when integrated with forest management protocols. Although further research is needed to refine biomass equations and explore emerging technologies such as Geiger Mode LiDAR, ALS has strong potential to enhance forest carbon crediting processes and support climate change mitigation goals.

Abstract The electric submersible pump (ESP) is a widely used artificial lift system to lift produced fluids from the wellbore to the surface. A typical ESP string consists, from top to bottom, of a single or multiple centrifugal pumps, gas handler devices, an intake, a protector, and a motor. The protector, also known as the seal section, is the primary barrier preventing well fluids from entering the motor. It also serves as an oil reservoir for the motor, equalizes internal and wellbore pressures, and transmits the pump thrust load. Consistent with industry practice, ExxonMobil historically deployed tandem 3-chamber protectors to provide redundant fluid isolation. By 2020, this configuration had been adopted in nearly all ESP installations. SLB and ExxonMobil jointly evaluated whether a newly engineered 4-chamber single protector could match or exceed tandem performance while reducing installation complexity. The assessment included chamber and shaft-seal design, oil-expansion behavior, thrust-bearing selection, and insights from dismantle, inspection and failure analysis (DIFA). A Ride Thrust Bearing (RTB) was selected to replace legacy high-load (HL) and glacier thrust bearings (GTB). This paper presents a multiyear field dataset showing that a single 4-chamber protector can outperform tandem 3-chamber protectors in large-scale unconventional applications. The transition across the ExxonMobil fleet, together with the low frequency of protector-related failures observed during the evaluation period, supports the technical viability of a simplified protector architecture. The results indicate that the 4-chamber design can improve system reliability while reducing installation complexity and operating cost in unconventional ESP applications.