Design GPTs:

Intelligent Engineering Solution Aid Design Platform - This platform rapidly constructs basic engineering solutions by integrating data from adjacent wells and engineering solutions within the same platform. Equipped with automated design writing capabilities, it simplifies the design process, reduces manual operations, and enhances design efficiency.

Optimization of Fracturing Design Solution Parameters - Combining geology with engineering, this system formulates personalized solutions based on the actual drilling trajectory of new wells and the superposition and contact relationships of different channel sand bodies. It optimizes segmented and clustered parameters, enhances fracture complexity, and maximizes fracture-controlled volume and effective sand body productivity. Simultaneously, it calculates bottomhole pressure and net pressure in real-time, promptly judges fracture propagation based on net pressure changes, predicts sand plugging risks, and dynamically optimizes construction parameters to ensure maximum single-well fracturing control volume.

Oil and Gas Field Development Design - This involves formulating detailed extraction plans for oil and gas fields based on actual conditions. It encompasses aspects such as extraction methods for oil and gas reservoirs, construction of production facilities, and design of process flows. The goal is to develop the optimal extraction plan that achieves efficient resource development while ensuring production safety and environmental protection.

Interpretation GPTs:

Real-time Prediction Platform for Optical Fiber Wellbore Leak Points - This software, integrating advanced sensing technology and deep learning algorithms, provides an efficient and precise real-time monitoring and early warning solution for the oil and gas industry, ensuring wellbore safety and reducing maintenance costs.

Reservoir/Lithology Identification - In oil and gas exploration, reservoirs are underground rock regions where oil and gas accumulate. Reservoir characteristics include lithology, physical properties, and hydrocarbon content, which are the primary directions for reservoir prediction. Lithology describes the mineral composition of reservoirs, reflecting storage performance and characteristics. Common parameters include physical structure, distribution, top interface morphology, and thickness. By integrating reservoir characteristics, predictions are made for hydrocarbon-rich zones (sweet spots), guiding drilling locations and extraction plans.

Intelligent Equipment Monitoring - Through an online monitoring system, real-time data on the operational status of workover rigs is monitored. This real-time capability not only provides technical support for field operators but also enables oilfield managers at all levels to promptly understand production site conditions, facilitating decision-making.

Identification of Geological/Engineering Sweet Spots - In oil and gas exploration and development, large areas of hydrocarbon-bearing zones and extensive hydrocarbon-bearing intervals are revealed. However, often only a portion is economically and technically viable for development, termed "sweet spots." Using measured geological and engineering parameters as inputs, neural network simulation technology and big data intelligent analysis are employed to interpret corresponding sweet spot evaluation parameters through correlation analysis of geological and elastic parameters.

Dynamic Evaluation of Artificially Induced Fracture Volume - This involves a comprehensive comparative assessment based on actual natural fracture responses, in-situ stresses, and brittleness conditions for each well and segment across platforms; qualitative and quantitative descriptions of artificial fracture complexity; and qualitative and quantitative assessments of fracture penetration.

Monitoring of Optical Fiber Liquid and Gas Production Profiles - Continuous oil fiber production profiling technology involves pre-pumping armored optical cables into continuous tubing, which is then transmitted to the target testing interval via continuous tubing units, enabling distributed optical fiber monitoring. Using the optical fiber itself as a sensor, this technology measures backscattered light to detect temperature and acoustic data along the fiber, facilitating real-time iterative analysis of wellbore fluid production and monitoring of production profiles for each cluster within oil and gas wells.

Dynamic Monitoring of Fracturing Sand and Fluid Influx - Utilizing distributed optical fibers already deployed in the same or adjacent wells, this technology monitors Distributed Acoustic Sensing (DAS) and Distributed Strain Sensing (DSS). DAS monitoring in the same well visually displays segment and cluster fluid and sand influx, guiding fracturing temporary plugging and转向 for optimal formation modification. Real-time monitoring of low-frequency strain signals depicts fracture development processes and states, guiding fracturing in real-time. Microseismic signal events are extracted to assess fracturing effects and optimize fracturing plans.

Process GPTs:

Intelligent Drilling Formation Analysis Platform - This platform integrates MWD and LWD data to provide precise geological guidance suggestions during drilling by analyzing geological layering information in real-time. It automatically generates alerts and warnings based on preset thresholds, ensuring engineers promptly adjust drilling parameters to mitigate risks. Additionally, through deep analysis of historical and real-time data, the system provides decision support for geological layering prediction and drilling parameter optimization, comprehensively enhancing drilling efficiency and safety.

EUR Prediction and Parameter Back-Calculation Platform Based on Fracturing Parameters - Utilizing advanced data analysis techniques combined with fracturing parameters, this system analyzes the Estimated Ultimate Recovery (EUR). Furthermore, it can reverse-calculate key parameters based on EUR values, enabling deep historical record mining and correlation analysis to optimize reservoir management and enhance recovery efficiency.

Drilling Parameter Optimization Platform - Based on well depth and drilling fluid performance, this platform recommends drill bit weight and drilling speed to maximize efficiency while ensuring safety. Adjustments to drill bit weight based on rock hardness are suggested to prevent excessive wear, while drilling speed is optimized according to rock drillability coefficients and rotation speed indices to ensure efficient drilling and reduce energy consumption.

Abnormal Formation Pressure Condition Alarm Platform - This system monitors formation pressure changes in real-time during drilling and immediately issues alerts upon detecting abnormalities, providing timely safety warnings for drilling operations. This helps prevent potential risks and ensures safe and smooth drilling operations.

Intelligent Sand Plugging Alarm Model Platform - Based on real-time data collection and transmission, combined with deep learning and edge computing technologies, this platform enables dynamic monitoring and early warning of sand plugging risks. Through efficient data analysis, it provides advance warnings and optimization suggestions, ensuring precise alerts and timely responses, thereby enhancing the efficiency and safety of sand plugging management. This solution facilitates the intelligent transformation of sand plugging management, providing a comprehensive solution for sand plugging issues in oil and gas extraction.

Intelligent Injection-Production Decision-Making - To improve water injection development efficiency, operators should integrate intelligent layered water injection systems with intelligent layered oil production systems. Through injection-production linkage and real-time monitoring of intelligent layered water injection and oil production, dynamic comparative analysis of water injection volumes, liquid production volumes, water content, and pressure across various layers is conducted, enhancing the targeted and flexible regulation of reservoirs.

Oil and Gas Field Video Monitoring - This system captures, intelligently recognizes, and actively warns against on-site violations in real-time, significantly reducing the need for supervisory personnel, improving regulatory efficiency, and effectively controlling safety risks. Electronic sand tables perceive risks in real-time, optimizing personnel allocation and objectively enhancing safety awareness and standardizing safety behaviors.

Artificial Lift Optimization - Artificial lift, crucial in crude oil extraction, brings oil and gas to the surface. Variations in wellbore structure, production, and fluid properties promote the diversification of artificial lift techniques. Intelligent lift optimization, combined with real-time wellbore monitoring solutions, maximizes well revenue by mitigating production decline rates.

Intelligent Mechanical Extraction Control - Based on IoT data, this system leverages big data technology, condition diagnosis technology, and mechanical extraction efficiency optimization technology to deeply mine the potential value of massive data, achieving overall control over the operational status and energy consumption of low-viscosity oil mechanical extraction wells.

Oil and Gas Field Energy Consumption Optimization - This involves promoting energy savings and consumption reduction in the four major production systems of mechanical extraction, water injection, gathering and transportation, and electricity, driving quality improvement and efficiency enhancement. Measures such as "shutdown, cessation, merger, transfer, and reduction," as well as wellbore process optimization, mechanical extraction well balance adjustment, and intermittent operation of low-production wells, are implemented to save electrical energy consumption in the mechanical extraction system. Electrical system distribution capacity reduction and replacement with energy-efficient motors are also adopted.

Production Scheduling Strategy Optimization - Oil extraction and processing are complex processes involving numerous steps and wide-ranging scopes. Daily production processes in oilfield enterprises require planned arrangements, necessitating the utilization of AI technology for intelligent operational scheduling. This ensures well-planned operations and construction in oilfield enterprises, guaranteeing orderly and efficient production and construction.

Proactive Equipment Fault Warning - The online monitoring system can analyze equipment operating status, predict equipment faults, and issue timely alerts, preventing downtime and extended repair times due to equipment failures.

Design-Oriented GPTs:

XX Oil and Gas Field Branch's Shale Gas Well Fracturing Project
In 2022, Anton provided fracturing engineering technology services for an oil and gas field branch, achieving an 18% synchronous increase in the average EUR (Estimated Ultimate Recovery) of shale gas wells in the Changning Block and a more than 10% year-on-year increase in the Yuxi Block. For tight gas wells utilizing new fracturing technologies, the average tested daily production per well reached 409,800 cubic meters, representing a 25% increase compared to conventional processes.

Explanatory GPTs:

Online Monitoring and Predictive Maintenance of Drilling and Workover Rigs
A predictive maintenance platform for drilling and workover rigs has been established to enable online equipment status monitoring (including intelligent early warning, intelligent diagnosis, intelligent assessment, etc.). This platform has already been successfully applied on CNOOC's offshore platforms.
Key Enhancement Directions:

Enhance the capability for sharing multi-source, heterogeneous information and data by establishing unified data service interfaces, information collection standards, data formats, and communication protocols, thereby achieving centralized and unified data management.
Boost the empowerment capabilities of AI technology application scenarios by developing algorithms and logical control models based on the big data platform and various subsystem application scenarios. These models will enable intelligent analysis, self-learning, and decision-making based on sensory information, facilitating predictive maintenance of key equipment.
Improve decision-making capabilities for risk management and control in drilling and workover rig operations.
Process-Oriented GPTs:

XX Deep Coalbed Methane Drilling Project
Anton commenced construction on the XX coal project in the third quarter of 2022, deploying two drilling rigs (50LDB with top drives). A total of 10 deep coalbed methane horizontal wells were drilled, with an average well depth of 3,530 meters and horizontal section lengths ranging from 1,000 to 1,500 meters. The average drilling cycle was 30.48 days (with the shortest being 27.58 days). Multiple single wells or drilling sequences set block records, earning high praise from the client.