Office Action Predictor
Last updated: April 16, 2026
Application No. 18/745,709

METHOD OF DETERMINING SATURATES, AROMATICS, RESINS, AND ASPHALTENE (SARA) FRACTIONS OF RESERVOIR FLUID DURING DOWNHOLE FLUID ANALYSIS

Non-Final OA §102§103
Filed
Jun 17, 2024
Examiner
FOX, DANIELLE A
Art Unit
2884
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Schlumberger Technology Corporation
OA Round
1 (Non-Final)
83%
Grant Probability
Favorable
1-2
OA Rounds
2y 7m
To Grant
96%
With Interview

Examiner Intelligence

Grants 83% — above average
83%
Career Allow Rate
590 granted / 711 resolved
+15.0% vs TC avg
Moderate +14% lift
Without
With
+13.5%
Interview Lift
resolved cases with interview
Typical timeline
2y 7m
Avg Prosecution
29 currently pending
Career history
740
Total Applications
across all art units

Statute-Specific Performance

§101
2.9%
-37.1% vs TC avg
§103
39.5%
-0.5% vs TC avg
§102
41.4%
+1.4% vs TC avg
§112
10.4%
-29.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 711 resolved cases

Office Action

§102 §103
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claim Objections Claim 15 is objected to because of the following informalities: Please end the claim with a period. Appropriate correction is required. Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claim(s) 1, 2, 5-9, 11-16, 19, and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by WO2020131996 (Molla). Regarding claim 1, Molla disclose a tool for estimating the saturates, aromatics, resins, and asphaltenes (SARA) fractions of a reservoir fluid, comprising: a flowbore housing (Fig. 1 and 2, 230); a filter array spectrometer coupled to the flowbore housing (Fig. 2, FILTER ARRAY SPECTROMETER); a fluorescence detector coupled to the flowbore housing (Fig. 2, FLUORESCENCE DETECTOR); a grating spectrometer coupled to the flowbore housing (Fig. 2, GRATING SPECTROMETER); a pressure and temperature gauge coupled to the flowbore housing (Fig. 2, P/T GAUGE); a resistivity sensor coupled to the flowbore housing (Fig. 2, RESISTIVITY SENSOR); and a viscosity sensor coupled to the flowbore housing (Fig. 2, DENSITY/VISCOSITY SENSOR). Regarding claim 2, Molla disclose the tool of claim 1, wherein the filter array spectrometer includes a light source (232), a filter array (236), and a detector array (236). Regarding claim 5, Molla disclose the tool of claim 1, wherein the grating spectrometer include a light source, a diffraction grating, and a detector, light source emits a light toward the diffraction grating, causing the light to diffract and specific angles based on wavelength [0024], and the detector measures the intensity of light at each wavelength, the intensity of light at each wavelength indicating a specific chemical in wellbore fluid [0020]. Regarding claim 6, Molla disclose the tool of claim 1, wherein the pressure and temperature gauge measures a force exerted by a fluid on a surface within the flowbore housing and a temperature of fluid within the flowbore housing (Fig. 2). Regarding claim 7, Molla disclose the tool of claim 1, wherein the resistivity sensor measures the electrical conductivity of fluid in the fluidbore housing (Fig. 2). Regarding claim 8, Molla disclose a method for estimating the saturates, aromatics, resins, and asphaltenes (SARA) fractions of a reservoir fluid, comprising: receiving first measurements for reservoir fluid (Fig. 3a, [0030]); training a regression model using a first subset of the first measurements (Fig. 3a, [0030]); testing the regression model using a second subset of the first measurements (Fig. 3a, [0030]); pumping wellbore fluid from a wellbore into a tool for analyzing reservoir fluid ([0033]-[0034]); receiving, from the tool, second measurements for reservoir fluid ([0033]-[0034]); inputting the second measurements into the regression model ([0033]-[0034]); and outputting SARA fraction levels from the regression model (Fig. 6, [0020], ([0033]-[0034]). Regarding claim 9, Molla disclose the method of claim 8, wherein the first measurements and second measurements include measurements of pressure, temperature, methane, ethane, propane, butane, pentane, hexanes, nitrogen, and carbon dioxide (Fig. 6, [0020], ([0033]-[0034]). Regarding claim 11, Molla disclose the method of claim 8, wherein the tool for analyzing reservoir fluid comprises: a flowbore housing (Fig. 1 and 2, 230); a filter array spectrometer coupled to the flowbore housing (Fig. 2, FILTER ARRAY SPECTROMETER); a fluorescence detector coupled to the flowbore housing (Fig. 2, FLUORESCENCE DETECTOR); a grating spectrometer coupled to the flowbore housing (Fig. 2, GRATING SPECTROMETER); a pressure and temperature gauge coupled to the flowbore housing (Fig. 2, P/T GAUGE); a resistivity sensor coupled to the flowbore housing (Fig. 2, RESISTIVITY SENSOR); and a viscosity sensor coupled to the flowbore housing (Fig. 2, DENSITY/VISCOSITY SENSOR). Regarding claim 12, Molla disclose the method of claim 11, wherein the filter array spectrometer, fluorescence detector, and grating spectrometer record wavelength and intensity measurements, and wherein the method further comprises identifying particles in the reservoir fluid based on the wavelength and intensity measurements [0020]. Regarding claim 13, Molla disclose the method of claim 8, wherein the pressure and temperature gauge measures a force exerted by a fluid on a surface within the flowbore housing and a temperature of fluid within the flowbore housing (Fig. 2). Regarding claim 14, Molla disclose the method of claim 8, wherein the resistivity sensor measures the electrical conductivity of fluid in the fluidbore housing (Fig. 2). Regarding claim 15, Molla disclose a system for estimating the saturates, aromatics, resins, and asphaltenes (SARA) fractions of a reservoir fluid, comprising: a tool for analyzing reservoir fluid (Fig. 1 and 2), comprising: a flowbore housing (Fig. 1 and 2, 230); a filter array spectrometer coupled to the flowbore housing (Fig. 2, FILTER ARRAY SPECTROMETER); a fluorescence detector coupled to the flowbore housing (Fig. 2, FLUORESCENCE DETECTOR); a grating spectrometer coupled to the flowbore housing (Fig. 2, GRATING SPECTROMETER); a pressure and temperature gauge coupled to the flowbore housing (Fig. 2, P/T GAUGE); a resistivity sensor coupled to the flowbore housing (Fig. 2, RESISTIVITY SENSOR); and a viscosity sensor coupled to the flowbore housing (Fig. 2, DENSITY/VISCOSITY SENSOR). a pump ([0019], [0022], [0034]); tubing inserted into a wellbore and coupled to the pump and the tool for analyzing reservoir fluid ([0019], [0022], [0034]). Regarding claim 16, Molla disclose the system of claim 15, wherein the filter array spectrometer includes a light source (232), a filter array (236), and a detector array (236). Regarding claim 19, Molla disclose the system of claim 15, wherein the grating spectrometer include a light source, a diffraction grating, and a detector, light source emits a light toward the diffraction grating, causing the light to diffract and specific angles based on wavelength [0024], and the detector measures the intensity of light at each wavelength, the intensity of light at each wavelength indicating a specific chemical in wellbore fluid [0020]. Regarding claim 20, Molla disclose the system of claim 15, wherein the pressure and temperature gauge measures a force exerted by a fluid on a surface within the flowbore housing and a temperature of fluid within the flowbore housing (Fig. 2). Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claim(s) 3, 4, 10, 17, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over WO2020131996 (Molla). Regarding claim 3, Molla disclose the tool of claim 2, but fail to explicitly teach wherein the detector array is one of a charge-coupled device sensor and a complementary metal-oxide semiconductor sensor, thereby allowing for that which is known in the art. However, CCD and CMOS are the most conventional array detector architectures in spectrometers. It would have been obvious to one of ordinary skill in the art at the time the invention was filed to elect commercially available imaging sensor technology to provide compact, low-power, and high-resolution detection. Regarding claim 4, Molla disclose the tool of claim 2, but fails to explicitly teach wherein the fluorescence detector includes an ultra-violet (UV) light emitter and a detector, the UV light emitter emits UV light that excites particles in fluid passing through the flowbore housing, and the detector measures the intensity and wavelength of light emitted by the excited particles. However, since Molla disclose analyzing hydrocarbon components, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to include a UV excitation source. One would have been motivated to include a UV Source because hydrocarbons fluoresce strongly under UV excitation, thereby improving detection sensitivity and selectivity. Regarding claim 10, Molla disclose the method of claim 8, but is silent with respect to wherein the regression model is one of a mean squared error, a mean absolute error, a root mean squared error, and an R-squared model, thereby allowing for that which is known in the art. Molla disclose training a regression model [0040] to predict fluid properties based on measured data. It would have been obvious to one of ordinary skill in the art at the time the invention was filed to implement the regression model as one based on MSE< MAE< RMSE, or R-squared metrics because these are well-known and routinely used statistical formulations and evaluation measures for regression modeling for predictive accuracy. One would have been motivated to select a predictable design choice for improving or assessing model performance. Regarding claim 17, Molla disclose the system of claim 16, but fail to explicitly teach wherein the detector array is one of a charge-coupled device sensor and a complementary metal-oxide semiconductor sensor, thereby allowing for that which is known in the art. However, CCD and CMOS are the most conventional array detector architectures in spectrometers. It would have been obvious to one of ordinary skill in the art at the time the invention was filed to elect commercially available imaging sensor technology to provide compact, low-power, and high-resolution detection. Regarding claim 18, Molla disclose the system of claim 16, but fails to explicitly teach wherein the fluorescence detector includes an ultra-violet (UV) light emitter and a detector, the UV light emitter emits UV light that excites particles in fluid passing through the flowbore housing, and the detector measures the intensity and wavelength of light emitted by the excited particles. However, since Molla disclose analyzing hydrocarbon components, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to include a UV excitation source. One would have been motivated to include a UV Source because hydrocarbons fluoresce strongly under UV excitation, thereby improving detection sensitivity and selectivity. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANI FOX whose telephone number is (571)272-3513. The examiner can normally be reached M-F: 9-5. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, David Makiya can be reached at 571-272-2273. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /DANI FOX/Primary Examiner, Art Unit 2884
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Prosecution Timeline

Jun 17, 2024
Application Filed
Feb 26, 2026
Non-Final Rejection — §102, §103
Mar 06, 2026
Interview Requested
Mar 24, 2026
Applicant Interview (Telephonic)
Mar 24, 2026
Examiner Interview Summary
Apr 06, 2026
Response Filed

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
83%
Grant Probability
96%
With Interview (+13.5%)
2y 7m
Median Time to Grant
Low
PTA Risk
Based on 711 resolved cases by this examiner. Grant probability derived from career allow rate.

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