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