Worked Example: Solution GOR (Rs) Correlation

The Standing correlation estimates solution gas-oil ratio from separator conditions. quantia propagates the uncertainty in stock-tank oil specific gravity through the full expression in one pass.

import quantia as qu
import quantia.math as qmath

# ── Correlation constants (Standing 1947) ───────────────────────────────────
a1, a2, a3, a4, a5 = 0.3818, -5.506, 2.902, 1.327, -0.7355

# ── Known exact inputs ───────────────────────────────────────────────────────
SG_g = 0.65                           # gas specific gravity (exact)
Tsp  = qu.Q(10.0, "°C").to("°F")    # separator temperature
Psp  = qu.Q(1.0, "atm").to("psi")   # separator pressure

# ── Uncertain input ──────────────────────────────────────────────────────────
with qu.config(n_samples=5000, seed=42):
    SG_o = qu.ProbUnitFloat.uniform(0.92, 0.96, "1")

# ── Correlation ──────────────────────────────────────────────────────────────
import math
log_Rst = (a1
         + a2 * qmath.log10(SG_o)
         + a3 * math.log10(SG_g)
         + a4 * math.log10(Psp.value)
         + a5 * math.log10(Tsp.value))

Rst = qmath.exp(log_Rst)   # ProbUnitFloat, dimensionless

# ── Results ──────────────────────────────────────────────────────────────────
print(f"Rs  mean : {Rst.mean():.4g}")
lo, hi = Rst.interval(0.95)
print(f"95% CI   : [{lo:.4g}, {hi:.4g}]")

# ── Save ─────────────────────────────────────────────────────────────────────
qu.save(Rst, "Rs_result.json")