Agent skill

api12-drilling-analyzer

Analyze drilling performance and metrics using API 12-digit well numbering system. Use for drilling time analysis, cost benchmarking, well comparison, sidetracks tracking, and drilling efficiency metrics across GOM fields.

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Forks 4

Install this agent skill to your Project

npx add-skill https://github.com/vamseeachanta/workspace-hub/tree/main/.claude/skills/data/energy/api12-drilling-analyzer

SKILL.md

Api12 Drilling Analyzer

When to Use

  • Parsing and validating API well numbers (10, 12, or 14 digit formats)
  • Analyzing drilling performance by operator, field, or area
  • Benchmarking drilling times and costs across similar wells
  • Tracking sidetrack wells and their relationship to parent bores
  • Calculating drilling efficiency metrics (ROP, NPT, connection time)
  • Comparing deepwater vs. shelf drilling performance
  • Identifying drilling hazards by area/block
  • Generating drilling AFE (Authorization for Expenditure) estimates

Core Pattern

API Number → Parse/Validate → Query BSEE Data → Analyze Drilling Metrics → Benchmark → Report

API Number Structure

Digits Description Example
1-2 State Code 17 = Louisiana (OCS)
3-5 County/Area Code 710 = Green Canyon
6-10 Well Sequence 49130
11-12 Sidetrack Number 00, 01, 02
13-14 Completion Number 00, 01 (14-digit only)

Implementation

Data Models

python
from dataclasses import dataclass, field
from datetime import date, timedelta
from typing import Optional, List, Dict, Any
from enum import Enum
import pandas as pd
import re

class APIFormat(Enum):
    """API number format types."""

*See sub-skills for full details.*
### Drilling Analyzer

```python
from typing import List, Dict, Optional
from pathlib import Path
import pandas as pd
import numpy as np
import logging

logger = logging.getLogger(__name__)

class DrillingAnalyzer:

*See sub-skills for full details.*
### Report Generator

```python
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from pathlib import Path

class DrillingReportGenerator:
    """Generate interactive drilling analysis reports."""

    def __init__(self, analyzer: DrillingAnalyzer):
        """

*See sub-skills for full details.*

## YAML Configuration

### Drilling Analysis Configuration

```yaml
# config/drilling_analysis.yaml

metadata:
  task: drilling_performance_analysis
  created: "2024-01-15"

wells:
  # List of API numbers to analyze
  - api: "177104913000"

*See sub-skills for full details.*
### AFE Configuration

```yaml
# config/afe_estimate.yaml

metadata:
  task: afe_estimation
  well_name: "Proposed Well A-1"

target_well:
  area: "Green Canyon"
  block: "640"

*See sub-skills for full details.*

## CLI Usage

### API Number Operations

```bash
# Parse and validate API number
python -m drilling_analyzer parse "177104913001"

# Find all sidetracks for a well
python -m drilling_analyzer sidetracks --api 1771049130

# List wells by area
python -m drilling_analyzer list --area GC --water-depth-min 5000

Benchmarking

bash
# Benchmark by area
python -m drilling_analyzer benchmark --by area --output reports/area_benchmark.html

# Benchmark by operator
python -m drilling_analyzer benchmark --by operator --min-wells 3

# Generate AFE estimate
python -m drilling_analyzer afe --td 25000 --water-depth 7000 --area GC

Reports

bash
# Generate comprehensive benchmark report
python -m drilling_analyzer report --config config/drilling_analysis.yaml

# Compare specific wells
python -m drilling_analyzer compare --apis 177104913000,177104913001,177590301100

# Generate efficiency metrics
python -m drilling_analyzer efficiency --output reports/efficiency.csv

Related Skills

  • bsee-data-extractor - Source data for drilling analysis
  • npv-analyzer - Economic analysis using drilling costs
  • production-forecaster - Link drilling to production outcomes
  • hse-risk-analyzer - Safety metrics for drilling operations

Sub-Skills

  • Example 1: Parse and Analyze API Numbers (+4)
  • API Number Handling (+3)

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