Cross-Border Joint Drilling Venture Document Parser for Egypt & UAE
Egypt and UAE discussed expanded oil and gas drilling programs. Build an automated cross-border document parsing and production yield estimator agent in Python that extracts drilling rights, concession sharing ratios, and target rig depths from bilateral agreements. Achieve 95%+ precision on concession clause extraction.
What you are building
The core problem, expected build, and operating context for this challenge.
Build an AI document parser in Python to analyze bilateral energy agreements and calculate yield expectations for Egypt-UAE joint drilling programs.
How work is evaluated
Evaluates joint venture terms extraction and entitlement calculations.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
bpd_sum_check
Verifies sum of partner net barrels equals total field production
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
extraction_precision
Precision of extracted contractual split percentages • target: 0.95 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Extract structured key terms from bilingual (Arabic/English) energy joint venture agreements.
Parse production sharing split ratios (e.g., 60/40 profit oil allocation).
Calculate projected net barrels of oil equivalent (BOE) output per partner.
Output standardized JV terms summary sheets for energy ministry reviews.
Reference links and supporting material
Sample Production Sharing Contract (PSC) terms for offshore Mediterranean and Gulf of Suez fields.
Challenge setup
Evaluates joint venture terms extraction and entitlement calculations.
Challenge input
JSON with partner_a, partner_b, total_bpd, cost_recovery_percent, and profit_split_percent
Python Document Tools
Parses structured parameters from energy contract texts.
Evaluated output
JSON with partner_a_net_bpd, partner_b_net_bpd, and contract_summary
- Verifies sum of partner net barrels equals total field production
- Precision of extracted contractual split percentages • target: 0.95 • range: 0-1
- Benchmark: LegalPscBench
- Extraction Precision target: 0.95
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
- Resemble AI · Required
- Synthflow · Optional
- Cekura · Optional
Evaluation contract
- bpd_sum_check · Weight 1
- extraction_precision · Weight 1
Metrics
- extraction_precision · Target 0.95
Benchmarks
- LegalPscBench
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON with partner_a, partner_b, total_bpd, cost_recovery_percent, and profit_split_percent
Output: JSON with partner_a_net_bpd, partner_b_net_bpd, and contract_summary
Execution harness: Python
Evaluation tools
- Python Document Tools · Text Extraction
Recipe freeze marker
No recipe freeze time is recorded.