IP Library › Granted Patent US 12,681,001
Granted Patent B2
US 12,681,001 · App. 18/764,515 · Granted Jul 14, 2026

Deep transient testing (DTT) downhole and surface gas rate integration workflow

Inventors: Adriaan Gerard Gisolf (Bucharest, RO); Bertrand Claude Emile Theuveny (Paris, FR); Francois Xavier Dubost (Paris, FR); Bei Gao (Shenzhen, CN); Maneesh Pisharat (Bucharest, RO); Ivan Fornasier (Paris, FR)
Assignee: Schlumberger Technology Corporation
G01N33/2823E21B21/067E21B21/08G01N9/00E21B2200/20
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Quick Facts
Patent No.
US 12,681,001
App. No.
18/764,515
Filed
Jul 5, 2024
Granted
Jul 14, 2026
Kind
B2
Art Unit
2855
USPC
73/32R
Abstract

Systems and methods presented herein generally relate to a formation testing platform for quantifying and monitoring deep transient testing (DTT) surface gas rates using formation testing data collected by a downhole well tool, which may be adjusted based on surface gas rates directly measured by surface equipment. For example, a method includes flowing one or more fluids from a subterranean formation to flow through a downhole well tool disposed in a wellbore of a well during a deep transient testing (DTT) operation performed by the downhole well tool. The method also includes measuring data related to one or more properties of the one or more fluids using one or more downhole fluid analysis sensors disposed within the downhole well tool, and predicting, via a control system, a first predicted DTT surface gas rate based on the data measured related to the one or more properties of the one or more fluids.

Claims (45)

1 . A method, comprising:

flowing one or more fluids from a subterranean formation to flow through a downhole well tool disposed in a wellbore of a well during a deep transient testing (DTT) operation performed by the downhole well tool;

measuring data related to one or more properties of the one or more fluids using one or more downhole fluid analysis sensors disposed within the downhole well tool;

predicting, via a control system, a first predicted DTT surface gas rate based on the data measured related to the one or more properties of the one or more fluids;

determining, via the control system, a total number of moles of gas released at a surface of the well for each component of each fluid of the one or more fluids by dividing a mass of each component of each fluid of the one or more fluids by molecular weight of the one or more fluids; and

determining, via the control system, a total volume of gas released at the surface of the well for each component of each fluid of the one or more fluids by multiplying the total number of moles for each component of each fluid of the one or more fluids by a molecular volume for each component of each fluid of the one or more fluids.

2 . The method of claim 1 , wherein the first predicted DTT surface gas rate comprises hydrocarbon content of the one or more fluids and gas emissions relating to the one or more fluids.

3 . The method of claim 1 , comprising:

detecting, via a gas meter of a mud-gas separator, surface measurement data relating to the one or more properties of the one or more fluids; and

predicting, via the control system, a second predicted DTT surface gas rate based on the surface measurement data relating to the one or more properties of the one or more fluids.

4 . The method of claim 1 , wherein the one or more fluids comprise an oil-based mud.

5 . The method of claim 1 , wherein the one or more fluids comprise a water-based mud.

6 . The method of claim 1 , wherein the downhole well tool comprises the control system, and wherein predicting the first predicted DTT surface gas rate comprises:

determining, via the downhole well tool, each fluid of the one or more fluids flowing through the downhole well tool;

mapping, via the downhole well tool, a flowrate to a fluid density estimation or fluid density measurement for each fluid of the one or more fluids;

summing, via the downhole well tool, flowrates of similar fluids of the one or more fluids; and

converting, via the downhole well tool, the summed flowrates from volume rates to mass rates by multiplying the volume rates to the fluid density estimation or fluid density measurement.

7 . The method of claim 6 , wherein the fluid density estimation or fluid density measurement comprises a direct measurement of fluid density via a fluid density sensor of the one or more downhole fluid analysis sensors.

8 . The method of claim 6 , wherein the fluid density estimation or fluid density measurement comprises an estimate of fluid density performed by the downhole well tool using one or more compositional measurements of the one or more fluids and a fluid model.

9 . The method of claim 1 , comprising determining, via the control system, a total volume of gas released at the surface of the well by summing the total volume of gas released at the surface of the well for each component of each fluid of the one or more fluids.

10 . The method of claim 1 , wherein the control system is a surface control system located at a surface of the well.

11 . The method of claim 1 , wherein the downhole well tool comprises the control system.

12 . The method of claim 1 , wherein the control system comprises a surface control system located at the surface of the well and a downhole control system disposed within the downhole well tool, and wherein the surface control system and the downhole control system are communicatively coupled.

13 . The method of claim 1 , further comprising:

flowing the one or more fluids to a surface of the well, wherein the one or more fluids comprise gas and mud; and

separating the gas and the mud of the one or more fluids at the surface using a separator.

14 . A method, comprising:

flowing one or more fluids from a subterranean formation to flow through a downhole well tool disposed in a wellbore of a well during a deep transient testing (DTT) operation performed by the downhole well tool;

measuring data related to one or more properties of the one or more fluids using one or more downhole fluid analysis sensors disposed within the downhole well tool;

predicting, via a control system, a first predicted DTT surface gas rate based on the data measured related to the one or more properties of the one or more fluids;

predicting, via the control system, a second predicted DTT surface gas rate based on measurement data detected by surface equipment of the well; and

calculating, via the control system, a vapor fraction for each gaseous component of the one or more fluids, by comparing the first predicted DTT surface gas rate and the second predicted DTT surface gas rate.

15 . The method of claim 14 , wherein the control system is a surface control system located at a surface of the well.

16 . The method of claim 14 , wherein the downhole well tool comprises the control system.

17 . A method, comprising:

flowing one or more fluids from a subterranean formation to flow through a downhole well tool disposed in a wellbore of a well during a deep transient testing (DTT) operation performed by the downhole well tool;

measuring data related to one or more properties of the one or more fluids using one or more downhole fluid analysis sensors disposed within the downhole well tool; and

predicting, via a control system, a first predicted DTT surface gas rate based on the data measured related to the one or more properties of the one or more fluids, wherein the downhole well tool comprises the control system, and wherein predicting the first predicted DTT surface gas rate comprises:

determining, via the downhole well tool, a weight fraction for each fluid of the one or more fluids at a plurality of time steps; and

determining, via the downhole well tool, a mass rate of each component of each fluid of the one or more fluids by multiplying the weight fraction for each component of each fluid of the one or more fluids by a total mass flowrate of the one or more fluids.

18 . The method of claim 17 , comprising:

determining, via the control system, a mass rate of gas released at a surface of the well by multiplying the mass rate of each component of each fluid of the one or more fluids with a vapor fraction of each component of each fluid of the one or more fluids; and

determining, via the control system, a total mass of gas released at the surface of the well for each component of each fluid of the one or more fluids by summing the mass rate of gas released at the surface of the well over total time of the plurality of time steps.

19 . The method of claim 17 , comprising determining, via the control system, a total mass pumped into the wellbore of the well for each component of each fluid of the one or more fluids by summing the mass rate of each component of each fluid of the one or more fluids over total time of the plurality of time steps.

20 . The method of claim 17 , wherein the control system is a surface control system located at a surface of the well.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 7, 2024
From: GISOLF, ADRIAAN GERARD; THEUVENY, BERTRAND CLAUDE EMILE; DUBOST, FRANCOIS XAVIER; GAO, BEI; PISHARAT, MANEESH; FOURNASIER, IVAN
To: SCHLUMBERGER TECHNOLOGY CORPORATION
Reel/Frame 067920/0778 →
Continuity (2)
Provisional Application 63512107 · Jul 6, 2023
Related Publication 20250012776A1 · Jan 9, 2025
References Cited (52)
US 5424959A · Reyes · 1995 [cited by applicant]
US 7081615B2 · Betancourt · 2006 [cited by applicant]
US 7526953B2 · Goodwin · 2009 [cited by applicant]
US 7920970B2 · Zuo · 2011 [cited by applicant]
US 7966273B2 · Hegeman · 2011 [cited by applicant]
US 8510242B2 · Al-Fattah · 2013 [cited by applicant]
US 8805617B2 · Zuo · 2014 [cited by applicant]
US 9128203B2 · Al-Dossary · 2015 [cited by applicant]
US 9322268B2 · Zuo · 2016 [cited by applicant]
US 9416647B2 · Zuo · 2016 [cited by applicant]
US 10073042B2 · Wang · 2018 [cited by applicant]
US 10316656B2 · Zuo · 2019 [cited by applicant]
US 10585082B2 · Zuo · 2020 [cited by applicant]
US 10781686B2 · Wang · 2020 [cited by applicant]
US 20090288881A1 · Mullins · 2009 [cited by applicant]
US 20100169020A1 · Niu · 2010 [cited by applicant]
US 20130103627A1 · Maddinelli · 2013 [cited by applicant]
US 20140110167A1 · Goebel · 2014 [cited by applicant]
US 20140238122A1 · Mostowfi · 2014 [cited by applicant]
US 20140360259A1 · Indo · 2014 [cited by applicant]
US 20150308264A1 · Zuo · 2015 [cited by applicant]
US 20160091389A1 · Zuo · 2016 [cited by applicant]
US 20160146004A1 · Wang · 2016 [cited by applicant]
US 20170269252A1 · Fang · 2017 [cited by applicant]
US 20200378814A1 · Layher · 2020 [cited by applicant]
US 20210285927A1 · Baecker · 2021 [cited by applicant]
US 20210324736A1 · Edmundson · 2021 [cited by applicant]
US 20230349286A1 · Jiang · 2023 [cited by examiner]
US 20230383649A1 · Valero · 2023 [cited by examiner]
US 20240401422A1 · Kaipov · 2024 [cited by examiner]
US 20250116589A1 · Gisolf · 2025 [cited by applicant]
EP 3685004A1 · 2020 [cited by applicant]
WO 2021081174A1 · 2021 [cited by applicant]
WO 2023064325A1 · 2023 [cited by applicant]
Zuo, J. Y. et al., “A New Fluid Property—Insitu Formation Volume Factors from Formation Testing”, SPWLA-2016-0000, presented at the 2016 SPWLA 57th Annual Logging Symposium, Reykjavik, Iceland, 15 pages. [cited by applicant]
Search Report and Written Opinion of International Patent Application No. PCT/US2024/036869 dated Oct. 18, 2024, 10 pages. [cited by applicant]
Search Report and Written Opinion of International Patent Application No. PCT/US2023/016362 Dated Jul. 26, 2023, 11 pages. [cited by applicant]
Bagheripour et al., Support Vector Regression Between PVT Data and Bubble Point Pressure. Journal of Petroleum Exploration and Production Technology, Mar. 2, 2014. pp. 227-231. [cited by applicant]
El-Sebakhy et al., Support Vector Machines Framework for Predicting the PVT Properties of Crude Oil Systems. SPE Middle East Oil and Gas Show and Conference, Mar. 11-14, 2007. Bahrain. SPE-105698. [cited by applicant]
Fayazi et al., State-of-the-Art Least Square Support Vector Machine Application for Accurate Determination of Natural Gas Viscosity. Industrial Engineering Chemistry Research, 2014 vol. 53, pp. 945-958. [cited by applicant]
Hegeman et al., Application of Artificial Neural Networks to Downhole Fluid Analysis. Feb. 2009, SPE Reservoir Evaluation and Engineering, pp. 7-13. SPE 123423. [cited by applicant]
Majidi et al., Evolving an Accurate Model Based on Machine Learning Approach for Prediction of Dew-Point Pressure in Gas Condensate Reservoirs. Chemical Engineering Research and Design, 2014 vol. 92 (5), pp. 891-902. [cited by applicant]
Osman et al. Prediction of Oil PVT Properties Using Neural Networks. SPE Middle East Oil Show. Mar. 17-20, 2001. 14 pages, Society of Petroleum Engineers, SPE-68233. [cited by applicant]
Siddigui, F., “A Derivative-less Approach for Generating Phase Envelopes”, Oil Gas Research, 2015, 1: 106, 6 pages. [cited by applicant]
Whitson, C. H. Characterizing Hydrocarbon Plus Fractions. Society of Petroleum Engineers Journal, 1983, 23(04), 683-694. SPE-12233. [cited by applicant]
Zuo et al., EOS-Based Downhole Fluid Characterization. Society of Petroleum Engineers Journal vol. 16 (1), Mar. 2011, pp. 115-124. [cited by applicant]
Zuo et al., Plus fraction characterization and PVT data regression for reservoir fluids near critical conditions. SPE Asia Pacific Oil and Gas Conference and Exhibition. Oct. 16-18, 2000, 12 pages, Society of Petroleum … [cited by applicant]
Notice of Allowance issued in U.S. Appl. No. 15/193,519 dated May 15, 2020, 9 pages. [cited by applicant]
Office Action issued in U.S. Appl. No. 15/193,519 dated Feb. 6, 2020, 7 pages. [cited by applicant]
Office Action issued in U.S. Appl. No. 15/193,519 dated Aug. 13, 2019, 10 pages. [cited by applicant]
Office Action issued in U.S. Appl. No. 15/193,519 dated Jan. 8, 2019, 15 pages. [cited by applicant]
Office Action issued in U.S. Appl. No. 15/193,519 dated Jun. 22, 2018, 29 pages. [cited by applicant]