petropy

Configured PetroPy formation evaluation

PetroPy 0.1.6 uses Log.fluid_properties() followed by Log.multimineral_model(). It does not provide the previously shown shale_volume, formation_porosity, water_saturation, permeability or to_las methods. Export a Log with write(...).

Environment and input contract

Use an isolated Python 3.11 environment with the metadata dependencies. The verified combination is PetroPy 0.1.6, lasio 0.30 and NumPy 1.26.4; lasio 0.32 removed add_curve, which PetroPy still calls. Old lasio 0.23/0.29 also fail with modern NumPy during header parsing. The cchardet prerelease has Python 3.11 wheels; dependency declarations in this skill do not install packages.

Before creating Log, prepare and inspect measured GR_N, NPHI_N, RHOB_N and RESDEEP_N. Their units are API, fraction v/v, g/cm³ and ohm·m. Input depth must be strictly increasing nonnegative feet of TVD below the well surface, with an identified datum, for these temperature/pressure correlations. The synthetic fixture is a vertical well where MD equals TVD. Deviated-well MD cannot be passed directly; establish a TVD/PVT treatment separately without silently resampling the logs. Convert percent neutron porosity explicitly. Do not rely on PetroPy's legacy density-porosity fallback: require a validated measured density curve before preconditioning. Keep missing measurements as NaN and retain their masks.

Run a configured model

The following function expects input satisfying that contract and a reviewed configuration. Declare depth_basis="tvd_below_surface" and depth_datum; the helper rejects an MD basis. example_config.json is a synthetic clean quartz/calcite calibration, not a default calibration for a field well. Adjust its interval, fluid parameters, mineral endpoints and weights using actual well/laboratory information before field use.

import json
import petropy as pp

def run_configured(las_path, config_path):
    with open(config_path, encoding='utf-8') as stream:
        config = json.load(stream)
    top, bottom = config['interval_ft']
    log = pp.Log(str(las_path))
    log.fluid_properties(top=top, bottom=bottom, **config['fluid'])
    log.multimineral_model(top=top, bottom=bottom, **config['multimineral'])
    return log

PetroPy 0.1.6 requires top and bottom to equal existing sampled depths, yet calculates on [top, bottom): the bottom sample remains unevaluated. Do not pass an arbitrary interval endpoint or describe all samples as evaluated. The library skips rows with missing required measurements; do not turn those rows into zero porosity, zero saturation or non-pay.

Validated helper and result checks

The formation evaluation helper validates normalized curve names/units, increasing feet depth, exact interval endpoints, explicit fluid/mineral calibration and positive density/resistivity. It runs the actual library, checks bulk and pore-volume closure, and writes LAS plus a JSON record of resolved parameters, interval, sample counts and source checksum. It rejects previously calculated model curves to prevent stale values surviving at missing or excluded samples.

python scripts/formation_evaluation.py normalized.las \
  --config reviewed_config.json --output evaluated.las

Resolve the script relative to the installed skill directory. Confirm for evaluated rows that matrix-mineral bulk volumes + BVCLAY + BVOM + BVPYR + PHIE sum to one, BVW + BVH equals PHIE, and SW/PHIE remain physical fractions. These are necessary consistency checks, not proof of a correct formation model.

Read calculations and pay intervals for the difference between bulk and matrix fractions and a stated thickness convention. Read fluid-property units before changing PVT inputs or interpreting fluid outputs. Standalone permeability, clustering, plotting and gas/shaly/organic-rich calibrations need separate validation.

Verification scope

Executed real LAS read/write, configured fluid calculation and two-mineral NNLS evaluation with project-generated observations. The analytic synthetic mixture is 65% quartz, 15% calcite and 20% water-filled pores. Tests check recovered fractions, conservation, feet-based temperature/pressure, NaN masks, interval edges and CLI failures. This is an API and physical-consistency baseline, not field calibration or a blanket validation of legacy PetroPy.

Official PetroPy implementation, checked against 0.1.6 on 2026-09-14.