TY  - JOUR
AU  - Kang, Qiang
AU  - He, Jiahuan
AU  - Tian, Xingwang
AU  - Yao, Hongyu
AU  - Tang, Ruilong
AU  - Tan, Jie
AU  - Yang, Hang
PY  - 2026
DA  - 2026/06/09
TI  - The Application Prospects of Embodied Intelligence in Oil and Gas Field Laboratories
JO  - Journal of Geo-Energy and Environment
T2  - Journal of Geo-Energy and Environment
JF  - Journal of Geo-Energy and Environment
VL  - 2
IS  - 3
SP  - 178
EP  - 184
DO  - 10.62762/JGEE.2026.553515
UR  - https://www.icck.org/article/abs/JGEE.2026.553515
KW  - laboratory
KW  - embodied intelligence
KW  - analytical testing
KW  - application prospects
KW  - challenges
AB  - Oil and gas testing laboratories have long encountered structural challenges including unclear functional roles, the disconnection between research and testing, and ongoing talent attrition, necessitating an intelligent transformation. Embodied intelligence, as an emerging paradigm integrating AI and robotics, features a local inference model of "cloud-device collaboration" that overcomes the limitations of traditional AI detached from the physical environment. Embodied intelligence enables laboratories to transition from "passive testing" to "proactive, intelligence-driven operations". Nonetheless, current deployment remains constrained by high costs and limited technological maturity. A phased, pilot-first implementation strategy is therefore recommended, prioritizing application validation in scenarios such as repetitive testing and high-risk operations. On this basis, the AI-driven "One-Person Laboratory" (OPL)—as a concrete manifestation of the "one-person company" concept within the scientific research domain—is expected to foster a new ecosystem of smart laboratories characterized by human-AI collaboration and complementary strengths, serving as a powerful supplement to the existing research system.
SN  - 3069-3268
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Kang2026The,
  author = {Qiang Kang and Jiahuan He and Xingwang Tian and Hongyu Yao and Ruilong Tang and Jie Tan and Hang Yang},
  title = {The Application Prospects of Embodied Intelligence in Oil and Gas Field Laboratories},
  journal = {Journal of Geo-Energy and Environment},
  year = {2026},
  volume = {2},
  number = {3},
  pages = {178-184},
  doi = {10.62762/JGEE.2026.553515},
  url = {https://www.icck.org/article/abs/JGEE.2026.553515},
  abstract = {Oil and gas testing laboratories have long encountered structural challenges including unclear functional roles, the disconnection between research and testing, and ongoing talent attrition, necessitating an intelligent transformation. Embodied intelligence, as an emerging paradigm integrating AI and robotics, features a local inference model of "cloud-device collaboration" that overcomes the limitations of traditional AI detached from the physical environment. Embodied intelligence enables laboratories to transition from "passive testing" to "proactive, intelligence-driven operations". Nonetheless, current deployment remains constrained by high costs and limited technological maturity. A phased, pilot-first implementation strategy is therefore recommended, prioritizing application validation in scenarios such as repetitive testing and high-risk operations. On this basis, the AI-driven "One-Person Laboratory" (OPL)—as a concrete manifestation of the "one-person company" concept within the scientific research domain—is expected to foster a new ecosystem of smart laboratories characterized by human-AI collaboration and complementary strengths, serving as a powerful supplement to the existing research system.},
  keywords = {laboratory, embodied intelligence, analytical testing, application prospects, challenges},
  issn = {3069-3268},
  publisher = {Institute of Central Computation and Knowledge}
}