JSON Well Completion Report

Level 2

Chapter 3: Data Structures

descriptionProblem

A multi-zone completion is described by a small JSON document: one record per perforated interval. Completion data arrives as JSON constantly (from the perforating contractor, the completion-design software, the well file), so reading it back into Python and summarising it is an everyday task.

The starter parses this completion for OD-003 into completion:

{
  "well": "OD-003",
  "field": "OML 58",
  "zones": [
    {"formation": "E2.0 Sand", "top_ft": 9650,  "bottom_ft": 9710,  "shots_per_ft": 6,  "perm_md": 250, "skin": 2.5},
    {"formation": "E3.0 Sand", "top_ft": 9820,  "bottom_ft": 9905,  "shots_per_ft": 12, "perm_md": 480, "skin": 1.0},
    {"formation": "E5.0 Sand", "top_ft": 10120, "bottom_ft": 10155, "shots_per_ft": 6,  "perm_md": 120, "skin": 4.0}
  ]
}

Write four functions that operate on the zones list:

net_pay_ft(zones): total perforated thickness (sum of bottom_ft − top_ft).
total_perforations(zones): total shots fired: thickness_ft × shots_per_ft, summed.
zone_flow_index(zone): a zone's relative flow capacity. A perforated

zone flows in proportion to its permeability-thickness and inversely with its skin (near-wellbore damage). Use perm_md × net_thickness_ft / (LN_RE_RW + skin), where LN_RE_RW = 7.0 is a typical drainage term, held constant.

flow_contribution(zones): a dict mapping each formation to its

percentage of the total flow index (the percentages sum to 100).

This tells you which zone is actually carrying the well: a thick, clean, high-perm zone can dominate flow even when the others add net pay.

lightbulbHints (0/3)

Stuck? Reveal hints one at a time — they progress from nudge to near-solution.

codeYour solution

main.py

import json

COMPLETION_JSON = """
{
  "well": "OD-003",
  "field": "OML 58",
  "zones": [
    {"formation": "E2.0 Sand", "top_ft": 9650,  "bottom_ft": 9710,  "shots_per_ft": 6,  "perm_md": 250, "skin": 2.5},
    {"formation": "E3.0 Sand", "top_ft": 9820,  "bottom_ft": 9905,  "shots_per_ft": 12, "perm_md": 480, "skin": 1.0},
    {"formation": "E5.0 Sand", "top_ft": 10120, "bottom_ft": 10155, "shots_per_ft": 6,  "perm_md": 120, "skin": 4.0}
  ]
}
"""

completion = json.loads(COMPLETION_JSON)

# ln(re/rw) - typical drainage term in the productivity denominator.
LN_RE_RW = 7.0

def net_pay_ft(zones):
    """Total perforated thickness across all zones, in feet."""
    # TODO
    pass

def total_perforations(zones):
    """Total shots = thickness_ft * shots_per_ft, summed over all zones."""
    # TODO
    pass

def zone_flow_index(zone):
    """Relative flow capacity: perm_md * net_thickness / (LN_RE_RW + skin)."""
    # TODO
    pass

def flow_contribution(zones):
    """Map each formation to its percent of total flow index (sums to 100)."""
    # TODO
    pass

print(f"Net pay:       {net_pay_ft(completion['zones'])} ft")
print(f"Perforations:  {total_perforations(completion['zones'])} shots")
print(f"Flow split:    {flow_contribution(completion['zones'])}")

visibilityReveal reference solutionexpand_more

Try solving it yourself first — the hints walk you through it. The solution below is one valid approach; yours may differ and still be correct.

import json

COMPLETION_JSON = """
{
  "well": "OD-003",
  "field": "OML 58",
  "zones": [
    {"formation": "E2.0 Sand", "top_ft": 9650,  "bottom_ft": 9710,  "shots_per_ft": 6,  "perm_md": 250, "skin": 2.5},
    {"formation": "E3.0 Sand", "top_ft": 9820,  "bottom_ft": 9905,  "shots_per_ft": 12, "perm_md": 480, "skin": 1.0},
    {"formation": "E5.0 Sand", "top_ft": 10120, "bottom_ft": 10155, "shots_per_ft": 6,  "perm_md": 120, "skin": 4.0}
  ]
}
"""

completion = json.loads(COMPLETION_JSON)

LN_RE_RW = 7.0


def net_pay_ft(zones):
    return sum(z["bottom_ft"] - z["top_ft"] for z in zones)


def total_perforations(zones):
    return sum((z["bottom_ft"] - z["top_ft"]) * z["shots_per_ft"] for z in zones)


def zone_flow_index(zone):
    thickness_ft = zone["bottom_ft"] - zone["top_ft"]
    return zone["perm_md"] * thickness_ft / (LN_RE_RW + zone["skin"])


def flow_contribution(zones):
    total = sum(zone_flow_index(z) for z in zones)
    return {z["formation"]: 100.0 * zone_flow_index(z) / total for z in zones}


# A formatted completion summary - the kind you'd paste into a well file.
print(f"Completion summary - {completion['well']} ({completion['field']})")
print(f"  Net pay:      {net_pay_ft(completion['zones']):>6.0f} ft")
print(f"  Perforations: {total_perforations(completion['zones']):>6.0f} shots")
for formation, pct in flow_contribution(completion["zones"]).items():
    print(f"  {formation:<12} {pct:5.1f}% of flow")

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