menu_book Chapters 6–7PetrophysicsArchieNet pay

Well-Log Quicklook → Net Pay

Turn a raw triple-combo log into shale volume, porosity, saturation and a net-pay count — the everyday petrophysics workflow.

What it does

Reads a well log (GR, density, neutron, resistivity), computes shale volume from GR, effective porosity from density–neutron, and water saturation from Archie's equation, then applies your cutoffs to flag net pay and sum the reservoir thickness.

How it works

1Shale volume from the gamma-ray between clean and shale endpoints.
2Effective porosity from the density–neutron average, corrected for shale.
3Water saturation from Archie's equation using porosity and resistivity.
4Apply V_sh, porosity and S_w cutoffs to flag net pay and total it.
5Display the composite log with net pay shaded — change any cutoff and re-run.

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Run it live

Runs entirely in your browser — no install. Edit any value and press Run to see the result change. This is the whole project; read it top to bottom.

well-log-quicklook.pystarting Python…

import numpy as np
import matplotlib.pyplot as plt

# ── A synthetic triple-combo log, standing in for a LAS file ─────────────
# In Ch 6-7 you load the real thing:  well = lasio.read("15-9-19.las")
rng = np.random.default_rng(7)
depth = np.arange(9000, 9100, 0.5)                     # ft
n = len(depth)
sand = ((depth > 9015) & (depth < 9045)) | ((depth > 9060) & (depth < 9082))
GR   = np.where(sand, 35, 95)  + rng.normal(0, 6, n)          # API
RHOB = np.where(sand, 2.30, 2.55) + rng.normal(0, 0.02, n)    # g/cc
NPHI = np.where(sand, 0.20, 0.32) + rng.normal(0, 0.01, n)    # v/v
RT   = np.where(sand, 25.0, 3.0) * np.exp(rng.normal(0, 0.15, n))  # ohm-m

# ── Interpretation parameters — tweak these and re-run ──────────────────
GR_clean, GR_shale = 30.0, 100.0        # GR endpoints for shale volume
rho_ma, rho_fl     = 2.65, 1.00         # matrix & fluid density
Rw, a, m, nexp     = 0.03, 1.0, 2.0, 2.0    # Archie constants
VSH_CUT, PHI_CUT, SW_CUT = 0.40, 0.08, 0.60  # NET-PAY cutoffs

# ── Petrophysics ────────────────────────────────────────────────────────
Vsh   = np.clip((GR - GR_clean) / (GR_shale - GR_clean), 0, 1)   # shale volume
phi_d = (rho_ma - RHOB) / (rho_ma - rho_fl)                       # density porosity
phi   = np.clip((phi_d + NPHI) / 2 * (1 - Vsh), 0.001, 0.40)      # effective porosity
Sw    = np.clip(((a * Rw) / (phi**m * RT)) ** (1 / nexp), 0, 1)   # Archie saturation

# ── Net pay: intervals that clear every cutoff ──────────────────────────
pay  = (Vsh <= VSH_CUT) & (phi >= PHI_CUT) & (Sw <= SW_CUT)
step = depth[1] - depth[0]
net_pay, gross = pay.sum() * step, depth[-1] - depth[0]

print(f"Gross interval : {gross:6.1f} ft")
print(f"Net pay        : {net_pay:6.1f} ft   (N/G = {net_pay/gross:.2f})")
print(f"Avg phi (pay)  : {phi[pay].mean():6.3f}")
print(f"Avg Sw  (pay)  : {Sw[pay].mean():6.3f}   ->  So = {1 - Sw[pay].mean():.2f}")

# ── Composite log display, net pay shaded gold ──────────────────────────
fig, ax = plt.subplots(1, 4, figsize=(9, 6), sharey=True)
panels = [(GR, "GR (API)", "green", False),
          (phi, "Porosity", "navy", False),
          (RT, "RT (ohm-m)", "firebrick", True),
          (Sw, "Sw", "black", False)]
for a_, (curve, title, color, logx) in zip(ax, panels):
    (a_.semilogx if logx else a_.plot)(curve, depth, color=color, lw=1)
    a_.set_title(title, fontsize=10)
    lo, hi = a_.get_xlim()
    a_.fill_betweenx(depth, lo, hi, where=pay, color="gold", alpha=0.30)
    a_.set_xlim(lo, hi); a_.grid(alpha=0.3)
ax[0].invert_yaxis(); ax[0].set_ylabel("Depth (ft)")
fig.suptitle(f"Well-Log Quicklook  -  net pay {net_pay:.1f} ft", fontweight="bold")
plt.tight_layout(); plt.show()

school

Want the full theory and the real-data version? Read the chapter this project is built from.

Read the chapter Companion repo