`pyrestoolbox`

A collection of Reservoir Engineering Utilities

This set of functions focuses on those that the author uses often while crafting programming solutions. These are the scripts that are often copy/pasted from previous work - sometimes slightly modified - resulting in a trail of slightly different versions over the years. Some attempt has been made here to make this implementation flexible enough such that it can be relied on as-is going forward.

Includes functions to perform simple calculations including;

Inflow for oil and gas
PVT Calculations for oil
PVT calculation for gas
Creation of Black Oil Table information
Creation of layered permeability distribution consistent with a Lorenze heterogeneity factor
Extract problem cells information from Intesect (IX) print files
Generation of AQUTAB include file influence functions for use in ECLIPSE
Creation of Corey and LET relative permeability tables in Eclipse format

This is the initial public release, with improvements and additions expected over time. Apologies in advance that it is only in oilfield units with no current plans to add multi-unit support.

Function List

Inflow	Gas Flow Rate Radial Gas Flow Rate Linear Oil Flow Rate Radial Oil Flow Rate Linear
Gas PVT	Gas Tc & Pc Calculation Gas Z-Factor Calculation Gas Viscosity Gas Viscosity * Z Gas Compressibility Gas Formation Volume Factor Gas Density Gas Water of Condensation Convert P/Z to P Convert Gas Gradient to SG Delta Pseudopressure Gas Condensate FWS SG
Oil PVT	Oil Density from MW Oil Critical Properties with Twu Incrememtal GOR post Separation Oil Bubble Point Pressure Oil GOR at Pb Oil GOR at P Oil Compressibility Oil Density Oil Formation Volume Factor Oil Viscosity Generate Black Oil Table data Estimate soln gas SG from oil Estimate SG of gas post separator Calculate weighted average surface gas SG
Brine PVT	Calculate suite of brine properties
Permeability Layering	Lorenz coefficient from Beta value Lorenz coefficient from flow fraction Lorenz coefficient to flow fraction Lorenz coefficient to permeability array
Simulation Helpers	Summarize IX convergence errors from PRT file Create Aquifer Influence Functions
Relative Permeability	Create sets of rel perm tables

Getting Started

Install the library with pip:

pip install pyrestoolbox

Import library into your project and start using.

A simple example below of estimating oil bubble point pressure.

>>> from pyrestoolbox import pyrestoolbox as rtb
>>> rtb.oil_pbub(api=43, degf=185, rsb=2350, sg_g =0.72, pbmethod ='VALMC')
5179.51086900132

A set of Gas-Oil relative permeability curves with the LET method

>>> import matplotlib.pyplot as plt
>>> df = rtb.rel_perm(rows=25, krtable='SGOF', krfamily='LET', kromax =1, krgmax =1, swc =0.2, sorg =0.15, Lo=2.5, Eo = 1.25, To = 1.75, Lg = 1.2, Eg = 1.5, Tg = 2.0)
>>> plt.plot(df['Sg'], df['Krgo'], c = 'r', label='Gas')
>>> plt.plot(df['Sg'], df['Krog'], c = 'g', label='Oil')
>>> plt.title('SGOF Gas Oil LET Relative Permeability Curves')
>>> plt.xlabel('Sg')
>>> plt.ylabel('Kr')
>>> plt.legend()
>>> plt.grid('both')
>>> plt.plot()

Or a set of Water-Oil relative permeability curves with the Corey method

>>> df = rtb.rel_perm(rows=25, krtable='SWOF', kromax =1, krwmax =0.25, swc =0.15, swcr = 0.2, sorw =0.15, no=2.5, nw=1.5)
>>> plt.plot(df['Sw'], df['Krow'], c = 'g', label='Oil')
>>> plt.plot(df['Sw'], df['Krwo'], c = 'b', label='Water')
>>> plt.title('SWOF Water Oil Corey Relative Permeability Curves')
>>> plt.xlabel('Sw')
>>> plt.ylabel('Kr')
>>> plt.legend()
>>> plt.grid('both')
>>> plt.plot()

A set of dimensionless pressures for the constant terminal rate Van Everdingin & Hurst aquifer, along with an AQUTAB.INC export for use in ECLIPSE.

>>> ReDs = [1.5, 2, 3, 5, 10, 25, 1000]
>>> tds, pds = rtb.influence_tables(ReDs=ReDs, export=True)
>>>
>>> for p, pd in enumerate(pds):
>>>     plt.plot(tds, pd, label = str(ReDs[p]))
>>>
>>> plt.xscale('log')
>>> plt.yscale('log')
>>> plt.legend(loc='upper left')
>>> plt.grid(which='both')
>>> plt.xlabel('Dimensionless Time (tD)')
>>> plt.ylabel('Dimensionless Pressure Drop (PD)')
>>> plt.title('Constant Terminal Rate Solution')
>>> plt.show()

Or creating black oil table information for oil

>>> results = rtb.make_bot_og(pi=4000, api=38, degf=175, sg_g=0.68, pmax=5000, pb=3900, rsb=2300, nrows=50)
>>> df, st_deno, st_deng, res_denw, res_cw, visw, pb, rsb, rsb_frac, usat = results['bot'], results['deno'], results['deng'], results['denw'], results['cw'], results['uw'], results['pb'], results['rsb'], results['rsb_scale'], results['usat']
>>> print('Stock Tank Oil Density:', st_deno, 'lb/cuft')
>>> print('Stock Tank Gas Density:', st_deng, 'lb/cuft')
>>> print('Reservoir Water Density:', res_denw, 'lb/cuft')
>>> print('Reservoir Water Compressibility:', res_cw, '1/psi')
>>> print('Reservoir Water Viscosity:', visw,'cP')

>>> fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(10,10))
>>> ax1.plot(df['Pressure (psia)'], df['Rs (scf/stb)'])
>>> ax2.plot(df['Pressure (psia)'], df['Bo (rb/stb)'])
>>> ax3.plot(df['Pressure (psia)'], df['uo (cP)'])
>>> ax4.semilogy(df['Pressure (psia)'], df['Co (1/psi)'])
>>> ...
>>> plt.show()
Stock Tank Oil Density: 52.05522123893805 lb/cuft
Stock Tank Gas Density: 0.052025361717109773 lb/cuft
Reservoir Water Density: 61.40223160167964 lb/cuft
Reservoir Water Compressibility: 2.930237693350768e-06 1/psi
Reservoir Water Viscosity: 0.3640686136171888 cP

And gas

>>> fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(10,10))
>>> ax1.semilogy(df['Pressure (psia)'], df['Bg (rb/mscf'])
>>> ax2.plot(df['Pressure (psia)'], df['ug (cP)'])
>>> ax3.plot(df['Pressure (psia)'], df['Gas Z (v/v)'])
>>> ax4.semilogy(df['Pressure (psia)'], df['Cg (1/psi)'])
>>> ...
>>> plt.show()

With ability to generate Live Oil PVTO style table data as well

>>> pb = 4500
>>> results = rtb.make_bot_og(pvto=True, pi=4000, api=38, degf=175, sg_g=0.68, pmax=5500, pb=pb, nrows=25, export=True)
>>> df, st_deno, st_deng, res_denw, res_cw, visw, pb, rsb, rsb_frac, usat = results['bot'], results['deno'], results['deng'], results['denw'], results['cw'], results['uw'], results['pb'], results['rsb'], results['rsb_scale'], results['usat']
>>>
>>> if len(usat) == 0:
>>>     usat_flag = False
>>> else:
>>>     usat_flag=True
>>>     usat_p, usat_bo, usat_uo = usat
>>>
>>> try:
>>>     pb_idx = df['Pressure (psia)'].tolist().index(pb)
>>>     bob = df['Bo (rb/stb)'].iloc[pb_idx]
>>>     rsb = df['Rs (mscf/stb)'].iloc[pb_idx]
>>>     uob = df['uo (cP)'].iloc[pb_idx]
>>>     cob = df['Co (1/psi)'].iloc[pb_idx]
>>>     no_pb = False
>>> except:
>>>     print('Pb was > Pmax')
>>>     no_pb = True
>>>
>>> print('Pb (psia):', pb)
>>> print('Bob (rb/stb):', bob)
>>> print('Rsb (mscf/stb):', rsb)
>>> print('Rsb Scaling Required:', rsb_frac)
>>> print('Visob (cP):', uob)
>>> print('Cob (1/psi):', cob,'\n')
>>> print('Stock Tank Oil Density:', st_deno, 'lb/cuft')
>>> print('Stock Tank Gas Density:', st_deng, 'lb/cuft')
>>> print('Reservoir Water Density:', res_denw, 'lb/cuft')
>>> print('Reservoir Water Compressibility:', res_cw, '1/psi')
>>> print('Reservoir Water Viscosity:', visw,'cP')
>>>
>>> fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(10,10))
>>> ax1.plot(df['Pressure (psia)'], df['Rs (mscf/stb)'])
>>> ax2.plot(df['Pressure (psia)'], df['Bo (rb/stb)'])
>>> ax3.plot(df['Pressure (psia)'], df['uo (cP)'])
>>> ax4.semilogy(df['Pressure (psia)'], df['Co (1/psi)'])
>>>
>>> ax1.plot([pb], [rsb], 'o', c='r')
>>> ax2.plot([pb], [bob], 'o', c='r')
>>> ax3.plot([pb], [uob], 'o', c='r')
>>> ax4.plot([pb], [cob], 'o', c='r')
>>>
>>> if usat_flag:
>>>     if no_pb == False:
>>>         for i in range(len(usat_bo)):
>>>             ax2.plot(usat_p[i], usat_bo[i], c='k')
>>>             ax3.plot(usat_p[i], usat_uo[i], c='k')
>>>
>>> fig.suptitle('Black Oil Properties')
>>> ..
>>> ..
>>> plt.show()
Pb (psia): 4500
Bob (rb/stb): 1.6072798403441817
Rsb (mscf/stb): 1.2863705330979234
Rsb Scaling Required: 0.9713981737449556
Visob (cP): 0.3422139569449832
Cob (1/psi): 5.711273668114706e-05

Stock Tank Oil Density: 52.05522123893805 lb/cuft
Stock Tank Gas Density: 0.052025361717109773 lb/cuft
Reservoir Water Density: 61.40223160167964 lb/cuft
Reservoir Water Compressibility: 2.930237693350768e-06 1/psi
Reservoir Water Viscosity: 0.3640686136171888 cP

Development

pyrestoolbox is maintained by Mark W. Burgoyne (https://github.com/mwburgoyne).

Comments

refactor oil sg equations to func and correct 141.4 -> 141.5 per standard API equation

There are 4 places in the source code where the oil/condensate specific gravity is calculated from the API. So I refactored those lines with the general equation near the top of the file.

def oil_sg(api_value: float) -> float: """ Returns oil specific gravity given API value of oil api_value: API value """ return 141.5 / (api_value+131.5)

The original 4 places the specific gravity was calculated using 141.4 (assume a typo). Petrowiki API Reference

Thank you for the repo and I will continue reading the source code!

opened by mwentzWW 1