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 .
Information Disclosure Statement
The listing of references in the specification is not a proper information disclosure statement. 37 CFR 1.98(b) requires a list of all patents, publications, or other information submitted for consideration by the Office, and MPEP § 609.04(a) states, "the list may not be incorporated into the specification but must be submitted in a separate paper." Therefore, unless the references have been cited by the examiner on form PTO-892, they have not been considered.
Specification
The attempt to incorporate subject matter into this application by reference to RU Patent Application No. 2022122482 is ineffective because the reference is to a foreign application.
The incorporation of essential material in the specification by reference to an unpublished U.S. application, foreign application or patent, or to a publication is improper. Applicant is required to amend the disclosure to include the material incorporated by reference, if the material is relied upon to overcome any objection, rejection, or other requirement imposed by the Office. The amendment must be accompanied by a statement executed by the applicant, or a practitioner representing the applicant, stating that the material being inserted is the material previously incorporated by reference and that the amendment contains no new matter. 37 CFR 1.57(g).
Claim Objections
Claims 3-6 and 11-14 are each objected to because of the following informalities: Each of claims 3-5 and 11-13 recite “stage (c).” However, elements (a)-(c) within each of independent claims 1 and 9, upon which claims 3-5 and 11-13 depend, have not been identified as “stages.” As such, deletion of the term “stage” in each of the noted claims is advised in order to clearly define the invention and use consistent terminology throughout the claims. Claims 6 and 14 are objected to herein by virtue of their dependency upon claims 5 and 13. Appropriate correction is required.
Claims 4 and 12 are each objected to because of the following informalities: Each of claims 4 and 12 recites “high-frequency sensors.” Independent claims 1 and 9, upon which claims 4 and 12, respectively, depend, recites “high-frequency pressure sensors.” Use of consistent language throughout the claims is advised to clearly associate the sensors of claims 4 and 12 with those of claims 1 and 9. Appropriate correction is required.
Claims 8 and 16 are each objected to because of the following informalities: Each of claims 8 and 16 recites “1 and 100 kHz.” It appears Applicant intends “1” to be in “kHz,” however, it is advised such should be added following “1” in order to clearly define such. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 and 9 each provide for the use of machine learning or a deep learning model, but since the claim does not set forth any steps involved in the method/process, it is unclear what method/process applicant is intending to encompass.
A claim is indefinite where it merely recites a use without any active positive steps delimiting how this use is actually practiced. Neither independent claim recites an active positive step associated with the use of machine learning or a deep learning model; as such, it is unclear as to how, for example machine learning/a deep learning model is intended to be used. Is data merely put into a computer? How does the machine learning/deep learning model used to “infer” the proppant concentration? Is the concentration estimated? A teaching in a prior art reference of machine learning or a deep learning model and method wherein proppant concentration is inferred will be considered to read on Applicant’s instantly claimed “use” thereof absent any further explanation and/or active step required and/or associated therewith.
Claims 2-8 and 10-19 are rejected by virtue of their dependency upon a rejected base claim.
Claims 3 and 11 each provide for the use of laboratory measurements, but since the claim does not set forth any steps involved in the method/process, it is unclear what method/process applicant is intending to encompass.
A claim is indefinite where it merely recites a use without any active positive steps delimiting how this use is actually practiced. It is unclear as to how laboratory measurements are “used” to perform stage (c). Is the mere use of data that is not necessarily obtained from a well, but rather, synthetic data, considered to be the use of laboratory measurements? Are the methods of claims 1 and 9 conducted in a lab and not within a wellbore? Clarification is required.
Claims 5 and 13 each provide for the use of a modeling approach, but since the claim does not set forth any steps involved in the method/process, it is unclear what method/process applicant is intending to encompass.
A claim is indefinite where it merely recites a use without any active positive steps delimiting how this use is actually practiced. It is unclear how a modeling “approach” is used to perform stage (c). Is the data merely collected in a computer and simulated? Are specific steps necessary for the approach to be considered a modeling approach? Is the running of a simulation/generation of simulated data considered to be the use of a modeling approach? Clarification is required.
Claims 6 and 14 are rejected by virtue of their dependency upon a rejected base claim.
Claims 6 and 14 each provide for the use of software, but since the claim does not set forth any steps involved in the method/process, it is unclear what method/process applicant is intending to encompass.
A claim is indefinite where it merely recites a use without any active positive steps delimiting how this use is actually practiced. It is unclear as to what is required of the software for such to be considered as “used” in the modeling approach. Is the mere use of a computer program considered to be the “use” of software? Clarification is required.
Claims 1-19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The term “high” in each of independent claims 1 and 9 is a relative term which renders the claim indefinite. The term “high” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The term “high” renders the scope of the claim indefinite as it is unclear as to what is required for a pressure sensor to be “high” frequency. Must it actively measure a particular frequency range? Be capable of use for measuring a particular frequency? Clarification is required. Claims 2-8 and 10-19 are rejected by virtue of their dependency upon a rejected base claim.
The preamble of claim 1 requires “A method for determining a proppant concentration in a fracturing fluid.” The body of the claim, however, rather requires the proppant concentration be inferred? It is unclear if Applicant intends “determining” and “inferring” to be one in the same and if indeed the body of the claim encompasses the method described by the preamble. It appears the proppant concentration of the steps of the claim can be estimated while determining in the preamble would appear to suggest the method encompasses active calculations/measurements that are made to provide a specific concentration value of proppant. Clarification is required. Claims 2-8 are rejected by virtue of their dependency upon a rejected base claim.
Claims 4 and 12 are each rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The term “high” in each of claims 4 and 12 is a relative term which renders the claim indefinite. The term “high” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The term “high” renders the scope of the claim indefinite as it is unclear as to what is required for a pressure sensor to be “high” frequency. Must it actively measure a particular frequency range? Be capable of use for measuring a particular frequency? Clarification is required.
Claims 6 and 14 are each rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claims 6 and 14 each contain the trademarks/trade names ANSYS and STAR-CCM+. Where a trademark or trade name is used in a claim as a limitation to identify or describe a particular material or product, the claim does not comply with the requirements of 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph. See Ex parte Simpson, 218 USPQ 1020 (Bd. App. 1982). The claim scope is uncertain since the trademark or trade name cannot be used properly to identify any particular material or product. A trademark or trade name is used to identify a source of goods, and not the goods themselves. Thus, a trademark or trade name does not identify or describe the goods associated with the trademark or trade name. In the present case, the trademark/trade name is used to identify/describe software and, accordingly, the identification/description is indefinite.
Claim 12 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 12 recites in line 2 “installed prior to a fracturing treatment.” However, claim 9, upon which claim 12 depends, requires “a fracturing treatment.” It is unclear if the fracturing treatment of claim 12 is intended to be the same as that of claim 9, in which case “a” should be replaced with -the-, or, if “a fracturing treatment” in claim 12 is separate from that of claim 9. Clarification is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-19 are rejected under 35 U.S.C. 101 because the claimed recitation of a use, without setting forth any steps involved in the process, results in an improper definition of a process, i.e., results in a claim which is not a proper process claim under 35 U.S.C. 101. See for example Ex parte Dunki, 153 USPQ 678 (Bd.App. 1967) and Clinical Products, Ltd. V Brenner, 255 F.Supp 131, 149 USPQ 475 (D.D.C. 1966).
The Examiner notes, each of claims 1, 3, 5, 6, 9, 11, 13 and 14 provide for the “use” of features including machine learning or a deep learning model (independent claims 1 and 9), laboratory measurements (dependent claims 3 and 11), a modeling approach (dependent claims 5 and 13) and software (dependent claims 6 and 14). None of the claims set forth any steps involved in the actual/active “use” thereof, and, as such, do not define a proper process.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claims 1-5, 9-13 and 17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Quan et al. (WO 2021/016412 A1).
With respect to independent claim 1, Quan et al. discloses a method for determining a proppant concentration in a fracturing fluid, comprising:
installing hydrophones or high-frequency pressure sensors in a tubular body ([0038]; [0059]);
flowing the fracturing fluid through the tubular body and measuring hydrodynamic acoustic noise spectra ([0036]; [0038]-[0039]; Quan et al. discloses the method uses vibrational energy which may be treated as noise that is induced by fluid pumping; since hydrodynamic acoustic noise spectra refers to the distribution of acoustic energy by the motion of liquids and Quan et al. provides for measuring the vibrational energy/detecting pumping noise with hydrophones, Quan et al. provides for the invention as claimed); and
using machine learning or a deep learning model to analyze the hydrodynamic acoustic noise spectra ([0017]; [0067]; [0075]-[0076]; [0081]; claim 25) and infer the proppant concentration in the fracturing fluid ([0006]; [0017]; [0024]; [0056]; [0069]; [0072]-[0074]; [0081]; wherein the at least one parameter includes proppant concentration/proppant amount).
With respect to independent claim 9, Quan et al. discloses a method for determining a proppant concentration in a fracturing fluid, comprising:
(a) installing hydrophones or high-frequency pressure sensors in a tubular body ([0038]; [0059]);
(b) flowing the fracturing fluid through the tubular body and measuring hydrodynamic acoustic noise spectra ([0036]; [0038]-[0039]; Quan et al. discloses the method uses vibrational energy which may be treated as noise that is induced by fluid pumping; since hydrodynamic acoustic noise spectra refers to the distribution of acoustic energy by the motion of liquids and Quan et al. provides for measuring the vibrational energy/detecting pumping noise with hydrophones, Quan et al. provides for the invention as claimed);
(c) using machine learning or a deep learning model to analyze the hydrodynamic acoustic noise spectra ([0017]; [0068]; [0075]-[0076]; [0081]; claim 25) and infer the proppant concentration in the fracturing fluid ([0005]-[0006]; [0017]; [0024]; [0056]; [0069]; [0072]-[0074]; [0081]; wherein the at least one parameter includes proppant concentration/proppant amount); and
(d) during the fracturing treatment, adjusting the proppant concentration ([0004]; [0005]; [0017]; [0067]; [0069]; [0072]; [0076]).
With respect to dependent claims 2 and 10, Quan et al. discloses wherein the tubular body comprises one as claimed ([0024]; [0038]; [0039]; [0043]-[0045]; [0059]; [0077]).
With respect to dependent claims 3 and 11, Quan et al. discloses wherein stage (c) is performed using laboratory measurements ([0077], wherein synthetic data is used).
With respect to dependent claims 4 and 12, Quan et al. discloses wherein the hydrophones or high frequency sensors are installed prior to a fracturing treatment and stage (c) is performed during the fracturing treatment ([0038]; [0059]).
With respect to dependent claims 5 and 13, Quan et al. discloses wherein stage (c) is performed using a modeling approach ([0077]).
With respect to dependent claim 17, Quan et al. discloses wherein the hydrodynamic acoustic noise spectra are measured at a surface of a subterranean well ([0038]-[0039]; [0059]).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 6 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Quan et al. as applied to claims 5 and 13, respectively, above, and further in view of Wise et al. (US 2016/0102528 A1).
Quan et al. discloses the method as set forth above with respect to each of claims 5 and 13, wherein a borehole model is created and a simulation is conducted to analyze the conductivity of the fracture-wellbore connection ([0077]; [0081]). The reference, however, fails to disclose what software is used for such modeling approaches. Wise et al. teaches methods for modeling complex hydraulic activities, including hydraulic fracturing (abstract) wherein various software is suggested as known and used to simulate data and provide virtual data capable of replicating real events; examples thereof include CAM, ANSYS and NEXUS reservoir simulation ([0003]). Since Quan et al. discloses the use of simulations and creates a model and Wise et al. suggests wherein software used to carry out modeling in complex activities such as hydraulic fracturing includes using software comprising ANSYS, it would have been obvious to one having ordinary skill in the art to try ANSYS in the method of Quan et al. in order to yield the predictable result of providing a reliable simulation and borehole model for use in analyzing the fracture-wellbore connection changes studied therein. When there is a design need or market pressure to solve a problem and there are a finite number of identified, predictable solutions, a person of ordinary skill has good reason to pursue the known options within his or her technical grasp. If this leads to the anticipated success, it is likely the product not of innovation but of ordinary skill and common sense.
Claims 7 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Quan et al. as applied to claims 1 and 9, respectively, above, and further in view of Dalamarinis et al. (WO 2021/016212 A1).
Quan et al. discloses the methods as set forth above with respect to claims 1 and 9, wherein the reference discloses capturing learning and applying machine learning to enhance delivery of alerts; the method can further be automated (0075]-[0076]). Data is further disclosed as used to infer and determine if it is necessary to alter the proppant concentration and behaviors are determined to train or program a machine to perform autodetection if such is necessary ([0081]). Quan et al. however, fails to explicitly disclose wherein the machine learning methods comprise a model as claimed. Dalamarinis et al. teaches methods of optimizing hydraulic fracturing by characterizing a fracture induced by pumping a fracturing fluid and analyzing properties of reflected tube waves detected in the well, wherein such can be sensed by pressure transducers such as hydrophones ([0060]); change is modeled with respect to a change in at least one parameter of the pumping fracturing fluid so as to train a machine learning algorithm to determine an optimized change in the at least one parameter (abstract). An example of a parameter to be optimized by such methods includes the amount of proppant pumped ([0048]; [0056]-[0057]). The machine learning models used for such a process are generally of a linear regression type ([0077]). Since both Quan et al. and Dalamarinis et al. teach methods of optimizing a hydraulic fracturing operation, wherein both utilize acoustic data related to fluid in the well that is obtained from sensors associated therewith, and both provide for the use of machine learning to improve mitigation/optimization recommendations, it would have been obvious to one having ordinary skill in the art to try a linear regression model as a component of the machine learning method of Quan et al. in order to optimize the adjusted proppant concentration determination disclosed therein as such a model is a model known to be used in machine learning methods associated with optimizing parameters of a hydraulic fracturing operation and thus would be expected to provide the information necessary to mitigate any adverse effects, such as non-optimal proppant concentration, present therein.
Claims 8, 16, 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Quan et al..
With respect to dependent claims 8 and 16, Quan et al. discloses the methods associated with claims 1 and 9, as set forth above, wherein it is suggested, the characteristics of the vibrational energy, such as frequency components, are affected by the properties of the system, including the connection between the well and the evolving fracture system; the energy is suggested as occurring at frequencies higher than can be measured with conventional fracture pumping data acquisition systems ([0008]). Quan et al. suggests wherein inducing tube waves in the disclosed method imparts pressure pulses into the well, wherein the pressure pulses may be a frequency modulated series, swept frequencies or single frequency pulses (Summary, [0001]). The reference additionally provides examples wherein frequencies are associated therewith ([0032]; [0078]). Although silent to a hydrodynamic acoustic noise spectra frequency range covered, and, thus, the range as claimed, since Quan et al. clearly suggests the hydrophones as measuring vibrational energy, wherein the energy is suggested as occurring at higher frequencies, as well as wherein the pressure pulses may be a frequency modulated series, swept frequencies or single frequency pulses, it is the position of the Office that one having ordinary skill in the art would recognize the optimal frequency range covered by the hydrodynamic acoustic noise spectra in order to effectively obtain measurements thereof suitable for use in obtaining information pertaining to proppant concentration so that such can be adjusted during the fracturing treatment when mitigation activity is necessary since it has been held "[W]here the general conditions of a claim are disclosed in the prior art, it is not inventive to discover the optimum or workable ranges by routine experimentation." In re Aller, 220 F.2d 454, 456, 105 USPQ 233, 235 (CCPA 1955). For more recent cases applying this principle, see Merck & Co. Inc. v. Biocraft Lab. Inc., 874 F.2d 804, 10 USPQ2d 1843 (Fed. Cir.), cert. denied, 493 U.S. 975 (1989); In re Kulling, 897 F.2d 1147, 14 USPQ2d 1056 (Fed. Cir. 1990); and In re Geisler, 116 F.3d 1465, 43 USPQ2d 1362 (Fed. Cir. 1997); Smith v. Nichols, 88 U.S. 112, 118-19 (1874) (a change in form, proportions, or degree "will not sustain a patent"); In re Williams, 36 F.2d 436, 438 (CCPA 1929) ("It is a settled principle of law that a mere carrying forward of an original patented conception involving only change of form, proportions, or degree, or the substitution of equivalents doing the same thing as the original invention, by substantially the same means, is not such an invention as will sustain a patent, even though the changes of the kind may produce better results than prior inventions."). See also KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 416 (2007) (identifying "the need for caution in granting a patent based on the combination of elements found in the prior art."). Additionally, the Examiner notes, obviousness can be shown in a predictable art when a difference between the claimed ranges is virtually negligible absent any showing of unexpected results or criticality. In re Brandt, 886 F. 3d 1171, 1177, 126 USPQ2d 1079, 1082 (Fed. Cir. 2018). The instant specification fails to explicitly establish the instantly claimed frequency range covered by the hydrodynamic noise spectra as critical, as exemplified by the extensiveness thereof, and it is unclear if any unexpected results are achieved by covering the entirety of such a frequency range. Since the frequency range covered by the hydrodynamic acoustic noise spectra of Quan et al. is sufficient for use in adjusting proppant concentration during a fracturing treatment, it does not appear that such would be considered an unexpected result of covering the frequency range instantly claimed, and, as such, the determination of optimal frequency range would be achievable through routine experimentation in the art.
With respect to dependent claims 18 and 19, Quan et al. discloses wherein in hydraulic fracturing, proppant can accumulate adjacent to perforations in a well and may partially or completely fill the well ([0024]); the disclosed invention seeks to prevent such and allow for normal pumping operations wherein proppant and fluid can easily flow through the casing/liner perforations and into fractures which are being extended into the formation ([0044]). For an operator, an open, hydraulically unimpeded wellbore is desirable ([0045]). The reference, however, fails to explicitly disclose the type proppant pack created by such a method and therefore fails to disclose the method as creating a homogeneous or heterogeneous proppant pack as claimed. Since Quan et al. seeks to provide for an open, hydraulically unimpeded wellbore, and since Applicant claims the only two alternatives which are possible for creating a proppant pack in a fracture, i.e., homogeneous or heterogeneous, it is the position of the Office that it would have been obvious to one having ordinary skill in the art to try to create either a homogeneous or heterogeneous proppant pack in a fracture when conducting the method of Quan et al. since such types of proppant packs are chosen from but a finite list of possibilities known to one having ordinary skill in the art for creating a proppant pack, and, would thus be expected to yield predictable results of providing for an open, hydraulically unimpeded wellbore.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
WO 2019/035858-A1 discloses the use of a computer system that takes into account measurements from hydrophones so as to determine operational parameters, such as a proppant concentration, to be altered to prevent damage from occurring during a fracturing operation.
WO 2019/222031-A1 discloses a microseismic monitoring job performed in real-time during hydraulic fracturing where results therefrom may be utilized to issue one or more signals to field equipment that may control one or more aspects of the hydraulic fracturing, such as proppant concentration.
US 2021/0087925 discloses the use of machine learning models to optimize parameters of a fracturing job, including proppant concentration.
WO 2018/117890 A1 discloses the use of FRACCADE framework to generate models that can be integrated with real-time data to optimize a proppant with one or more operational constraints so a to optimize a stimulation design. Seismic energy including vibrations associated with fluid flow, i.e., fluid flow noise, can be sensed and used as the real-time data integrated with the model.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Angela M DiTrani Leff whose telephone number is (571)272-2182. The examiner can normally be reached Monday-Friday, 9AM-5PM.
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, Doug Hutton can be reached at 5712724137. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Angela M DiTrani Leff/Primary Examiner, Art Unit 3674
ADL
01/22/26