AI-301 · Source-linked project profile. Read the scope, reported result and what remains unknown.
Open the interactive projectHow to read this evidenceSLB describes Azule using one digital workflow from well design through rig execution offshore Angola.
Supplier reports 95% of engineering tasks automated, planning time of 192 versus 31 hours and 75% fewer manual handoffs. A 2,000-meter section had zero reported nonproductive time and 16% higher net rate of penetration than the field benchmark. These are different measures, not a common financial return.
No well identifier, wider well population, benchmark construction, review-effort adjustment, quality comparison or full cost. Execution is described as autonomous, but approval, override and fallback rules are undisclosed. No LLM or AI-only contribution is established; zero NPT for this section is not a long-term reliability rate. Q3 release published 23 October 2026. The related case study is undated. One well and a 2,000-meter section are described; exact operating dates unknown.
Does passing an approved plan into rig execution reduce total work once checking, exceptions and overrides are counted?
PDF p. 16: Eni, Azule, ADNOC and BSP Digital highlights; PDF p. 14: production chemistry. HTML release has the same paragraphs.
Location; Results: Achieving operational excellence; Products Used: DrillOps AI-driven workflows.
SLB describes Azule using one digital workflow from well design through rig execution offshore Angola.
No well identifier, wider well population, benchmark construction, review-effort adjustment, quality comparison or full cost. Execution is described as autonomous, but approval, override and fallback rules are undisclosed. No LLM or AI-only contribution is established; zero NPT for this section is not a long-term reliability rate.
A source grade describes provenance, not independent verification. This is a research profile, not a measure of net return. Report a correction.