IP Library Granted Patent US 12,153,003
Granted Patent B2
US 12,153,003 · App. 17/937,309 · Granted Nov 26, 2024

Method to determine a mass of an absorbed gas and a mass of a pore gas in a sample

Inventors: Jin-Hong Chen (Katy, TX); Stacey M. Althaus (Houston, TX); Mohammed Boudjatit (El Kennar, DZ); Houzhu Zhang (Houston, TX)
Assignee: SAUDI ARABIAN OIL COMPANY
G01N24/081E21B7/04E21B47/022G01N33/241G01N33/246E21B2200/20
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Quick Facts
Patent No.
US 12,153,003
App. No.
17/937,309
Granted
Nov 26, 2024
Kind
B2
Abstract

A method and system for determining a mass of an absorbed gas and a mass of a pore gas in a sample using NMR spectroscopy is provided. The method includes acquiring a baseline NMR spectrum of a pressure cell containing the sample, saturating the sample with a gas, acquiring a saturated NMR spectrum and determining a differential NMR spectrum of the sample by subtracting the baseline NMR spectrum from the saturated NMR spectrum. The method also includes separating the differential NMR spectrum into an absorbed gas NMR spectrum to determine an absorbed gas NMR signal and a pore gas NMR spectrum to determine a pore gas NMR signal by performing a spectral deconvolution. The method further includes acquiring a normalization NMR spectrum of the pressure cell containing a gas to determine a gas calibration NMR signal and determining the mass of the absorbed gas and pore gas.

Claims (74)

1. A method of determining a mass of an absorbed gas and a mass of a pore gas in a sample using nuclear magnetic resonance (NMR) spectroscopy, the method comprising:

acquiring a baseline NMR spectrum of a pressure cell containing the sample;

creating a gas saturated sample in the pressure cell;

acquiring a saturated NMR spectrum of the pressure cell containing the gas saturated sample;

determining a differential NMR spectrum of the sample by subtracting the baseline NMR spectrum from the saturated NMR spectrum;

separating the differential NMR spectrum into an absorbed gas NMR spectrum and a pore gas NMR spectrum by performing a spectral deconvolution;

determining an absorbed gas NMR signal based, at least in part, on the absorbed gas NMR spectrum and a pore gas NMR signal based, at least in part, on the pore gas NMR spectrum;

acquiring a normalization NMR spectrum of the pressure cell containing a gas injected at a predetermined measurement pressure;

determining a gas calibration NMR signal based, at least in part, on the normalization NMR spectrum; and

determining the mass of the absorbed gas and the mass of the pore gas based, at least in part, on the absorbed gas NMR signal, the pore gas NMR signal and the gas calibration NMR signal.

2. The method of claim 1 , further comprising determining a reservoir characteristic of the sample, based at least in part, the mass of the absorbed gas and the mass of the pore gas, wherein the reservoir characteristic comprises a porosity, a composition, a water and a hydrocarbon content, a permeability, or an injected fluid behavior.

3. The method of claim 2 , further comprising:

generating a reservoir model, using a reservoir modeler based, at least in part, on the reservoir characteristic;

performing a reservoir simulation, using a reservoir simulator, to determine a drilling target based, at least in part, on the reservoir model;

planning a wellbore path, using a wellbore path planning system, to intersect the drilling target; and

drilling a wellbore, guided by the wellbore path, using a drilling system.

4. The method of claim 1 , wherein the sample is a rock core sample.

5. The method of claim 1 , wherein creating the gas saturated sample in the pressure cell comprises injecting a gas at the predetermined measurement pressure into the pressure cell containing the sample until the saturated NMR spectrum stabilizes.

6. The method of claim 5 , wherein the gas is a hydrocarbon gas.

7. The method of claim 1 , wherein separating the differential NMR spectrum into the absorbed gas NMR spectrum and the pore gas NMR spectrum by performing the spectral deconvolution comprises:

fitting a first Lorentzian curve to a broad peak of the differential NMR spectrum to obtain the absorbed gas NMR spectrum; and

fitting a second Lorentzian curve to a narrow peak of the differential NMR spectrum to obtain the pore gas NMR spectrum.

8. A non-transitory computer readable memory, having computer-executable instructions stored thereon that, when executed by a processor, perform steps comprising:

acquiring a baseline NMR spectrum of a pressure cell containing a sample;

creating a gas saturated sample in the pressure cell;

acquiring a saturated NMR spectrum of the pressure cell containing the gas saturated sample;

determining a differential NMR spectrum of the sample by subtracting the baseline NMR spectrum from the saturated NMR spectrum;

separating the differential NMR spectrum into an absorbed gas NMR spectrum and a pore gas NMR spectrum by performing a spectral deconvolution;

determining an absorbed gas NMR signal based, at least in part, on the absorbed gas NMR spectrum and a pore gas NMR signal based, at least in part, on the pore gas NMR spectrum;

acquiring a normalization NMR spectrum of the pressure cell containing a gas injected at a predetermined measurement pressure;

determining a gas calibration NMR signal based, at least in part, on the normalization NMR spectrum; and

determining a mass of an absorbed gas and a mass of a pore gas based, at least in part, on the absorbed gas NMR signal, the pore gas NMR signal and the gas calibration NMR signal; and

determining a reservoir characteristic of the sample based, at least in part, the mass of the absorbed gas and the mass of the pore gas.

9. The non-transitory computer readable memory of claim 8 , wherein the steps further comprise:

generating a reservoir model using a reservoir modeler based, at least in part, on the reservoir characteristic;

performing a reservoir simulation to determine a drilling target based, at least in part, on the reservoir model; and

planning a wellbore path, using a wellbore path planning system, to intersect the drilling target.

10. The non-transitory computer readable memory of claim 8 , wherein the reservoir characteristic comprises a porosity, a composition, a water and a hydrocarbon content, a permeability, or an injected fluid behavior.

11. The non-transitory computer readable memory of claim 8 , wherein the sample is a rock core sample.

12. The non-transitory computer readable memory of claim 8 , wherein creating the gas saturated sample in the pressure cell comprises injecting a gas at the predetermined measurement pressure into the pressure cell containing the sample until the saturated NMR spectrum stabilizes.

13. The non-transitory computer readable memory of claim 12 , wherein the gas is a hydrocarbon gas.

14. The non-transitory computer readable memory of claim 8 , wherein separating the differential NMR spectrum into the absorbed gas NMR spectrum and the pore gas NMR spectrum by performing the spectral deconvolution comprises:

fitting a first Lorentzian curve to a broad peak of the differential NMR spectrum to obtain the absorbed gas NMR spectrum; and

fitting a second Lorentzian curve to a narrow peak of the differential NMR spectrum to obtain the pore gas NMR spectrum.

15. A system, comprising:

a pressure cell;

a sample configured to be inserted into the pressure cell;

an NMR pressure and injection system configured to:

establish a predetermined measurement pressure within the pressure cell, and

create a gas saturated sample in the pressure cell; and

an NMR control and data acquisition system configured to:

acquire a baseline NMR spectrum of the pressure cell containing the sample;

acquire a saturated NMR spectrum of the pressure cell containing the gas saturated sample;

determine a differential NMR spectrum of the sample by subtracting the baseline NMR spectrum from the saturated NMR spectrum;

separate the differential NMR spectrum into an absorbed gas NMR spectrum and a pore gas NMR spectrum by performing a spectral deconvolution;

determine an absorbed gas NMR signal based, at least in part, on the absorbed gas NMR spectrum and a pore gas NMR signal based, at least in part, on the pore gas NMR spectrum:

acquire a normalization NMR spectrum of the pressure cell containing the gas saturated sample;

determine a gas calibration NMR spectrum based, at least in part, on the normalization NMR spectrum;

determine a gas calibration NMR signal based, at least in part, on the normalization NMR spectrum;

determine a mass of an absorbed gas and a mass of a pore gas based, at least in part, on the absorbed gas NMR signal, the pore gas NMR signal and the gas calibration NMR signal, and

determine a reservoir characteristic of the sample based, at least in part, on the mass of the absorbed gas and the mass of the pore gas.

16. The system of claim 15 , further comprising:

a reservoir modeler configured to produce a reservoir model based, at least in part, on the reservoir characteristic;

a reservoir simulator configured to:

produce a reservoir simulation based, at least in part, on the reservoir model, and

determine a drilling target based, at least in part, on the reservoir simulation;

a wellbore path planning system configured to plan a wellbore path to intersect the drilling target of a subterranean region of interest; and

a wellbore drilling system configured to drill a wellbore guided by the wellbore path.

17. The system of claim 15 , wherein the sample is a rock core sample and the reservoir characteristic comprises a porosity, a composition, a water and a hydrocarbon content, a permeability, or an injected fluid behavior.

18. The system of claim 15 , wherein creating the gas saturated sample in the pressure cell comprises injecting a gas at the predetermined measurement pressure into the pressure cell containing the sample until the saturated NMR spectrum stabilizes.

19. The system of claim 18 , wherein the gas is a hydrocarbon gas.

20. The system of claim 15 , wherein separating the differential NMR spectrum into the absorbed gas NMR spectrum and the pore gas NMR spectrum by performing the spectral deconvolution comprises:

fitting a first Lorentzian curve to a broad peak of the differential NMR spectrum to obtain the absorbed gas NMR spectrum; and

fitting a second Lorentzian curve to a narrow peak of the differential NMR spectrum to obtain the pore gas NMR spectrum.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 18, 2023
From: SAUDI ARAMCO UPSTREAM TECHNOLOGIES COMPANY
To: SAUDI ARABIAN OIL COMPANY
Reel/Frame 065268/0033 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 17, 2023
From: ARAMCO SERVICES COMPANY
To: SAUDI ARAMCO UPSTREAM TECHNOLOGIES COMPANY
Reel/Frame 065255/0383 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 16, 2023
From: CHEN, JIN-HONG; ALTHAUS, STACEY M.; ZHANG, HOUZHU
To: ARAMCO SERVICES COMPANY
Reel/Frame 063970/0104 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 16, 2023
From: BOUDJATIT, MOHAMMED
To: SAUDI ARABIAN OIL COMPANY
Reel/Frame 063970/0161 →
Continuity (1)
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