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 .
DETAILED ACTION
1. The amendment filed on 01/07/2026 has been received and considered. Claims 1-15 are presented for examination.
Drawings
2. The drawings are objected to because in replacement Fig. 2 "WH 2” is placed over the arrow without a blank space. 37 C.F.R. § 1.84(p)(2) requires "Numbers, letters, and reference characters must measure at least .32 cm. (1/8 inch) in height. They should not be placed in the drawing so as to interfere with its comprehension. Therefore, they should not cross or mingle with the lines. They should not be placed upon hatched or shaded surfaces. When necessary, such as indicating a surface or cross section, a reference character may be underlined and a blank space may be left in the hatching or shading where the character occurs so that it appears distinct." Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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.
3. Claims 1-18 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.
As per Claim 1 and 18, they recite the limitation “satisfies constraints of the surface network solved by the surface simulator in the different simulation scenario” which is vague and indefinite since "satisfies" does not set a range.
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.
4. Claims 1-3, 5-6, 9-10, and 13-15, 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Guyaguler et al. (US 8805660 B2), in view of Kohler et al. (“SimProxy Decision Support System: A Neural Network Proxy Applied to Reservoir and Surface Integrated Optimization”), and further in view of Cadena et al. (“A Simple Procedure to Develop Analytical Curves of IPR from Reservoir Simulators with Application in Production Optimization”).
As per Claim 1 and 18, Guyaguler et al. taches a method/ computer system of generating a reservoir performance forecast (Title, Col. 9 lines 35-67, Col. 10 lines 1-30), the method comprising:
(Claim 18) one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions that when executed by the one or more processors cause the system (Title, Col. 9 lines 35-67, Col. 10 lines 1-30, Col. 12 lines 14-49) to:
a) initiating a full physics-based simulation using a subsurface simulator with a corresponding subsurface model representing a subsurface and one or more wells fluidly connecting to the subsurface (Col. 1 lines 24-43, Col. 8 lines 61-67, Col. 9 lines 1-5, “the use of external commercial surface facility network simulators… the reservoir can be modeled with a full-field commercial finite-difference reservoir simulator and the surface facilities can be modeled with a commercial non-transient network simulator”);
b) generating inflow performance relationship data for each well at each time step during the full physics-based subsurface simulation, wherein the inflow performance relationship data comprises performance data for at least one phase of fluid for each well (Col. 1 lines 24-43, Col. 6 lines 32-48, Col. 10 lines 60-67, Col. 11 lines 1-25, “"reservoir simulations" refer to mathematical representations of fluid flow (e.g., oil, gas, water)”, “A discretized IPR is generated for multiple pressure constraints in step 25. For steps 23,25, the sub-domain is solved with a timestep size … The sub-domain solve can be considered the same as creating a separate near-well model and then simulating this model with the appropriate boundary conditions. For example, for ten IPR points, ten sub-domain solves are carried out, which are equivalent to completing ten completely independent simulations on a small grid, but in the same process.”, “The IPR passed on to the surface facility network simulator typically includes a table with pressure (bottomhole or tubing head) and surface rates as columns. Each row in the table is a point on the IPRs at a particular pressure value.”: Examiner’s note – constructing an inflow performance relationship that reflects the near-well reservoir conditions at the endo f the timestep by solving each sub-domain repeatedly over the same timestep with different well constrains);
c) generating an inflow performance relationship database with the generated inflow performance relationship data for each well at each time step during the full physics-based subsurface simulation (Col. 9 lines 28-54, Col. 11 lines 1-25, “A discretized IPR is generated for multiple pressure constraints in step 25. For steps 23,25, the sub-domain is solved with a timestep size … The sub-domain solve can be considered the same as creating a separate near-well model and then simulating this model with the appropriate boundary conditions. For example, for ten IPR points, ten sub-domain solves are carried out, which are equivalent to completing ten completely independent simulations on a small grid, but in the same process.”, “The IPR passed on to the surface facility network simulator typically includes a table with pressure (bottomhole or tubing head) and surface rates as columns. Each row in the table is a point on the IPRs at a particular pressure value. ”: Examiner’s note - generating structured IPR table for each well at each coupling period.); and
d) … wherein the reservoir performance forecast satisfies constraints of the surface network solved by the surface simulator in the different simulation scenario (Col. 1 lines 24-43, Col. 1 lines 3-20, Col. 9 lines 28-54 Col. 1 lines 24-43, Col. 9 lines 38-54 , “A discretized IPR is generated for multiple pressure constraints in step 25. For steps 23,25, the sub-domain is solved with a timestep size … The sub-domain solve can be considered the same as creating a separate near-well model and then simulating this model with the appropriate boundary conditions. For example, for ten IPR points, ten sub-domain solves are carried out, which are equivalent to completing ten completely independent simulations on a small grid, but in the same process.”).
Guyaguler et al. fails to teach explicitly d) generating a reservoir performance forecast for a different simulation scenario using the subsurface simulator, wherein the subsurface simulator uses the inflow performance relationship database as a proxy to represent the subsurface in the different simulation scenario, ….
Cadena et al. teaches d) generating a reservoir performance forecast for a different simulation scenario using the subsurface simulator, wherein the subsurface simulator uses the inflow performance relationship database as … to represent the subsurface in the different simulation scenario, wherein the reservoir performance forecast satisfies constraints of the surface network solved by the surface simulator in the different simulation scenario (right column on Pg 631 “One application of IPR is a production optimization method … to choose the best value of production parameters such as tubing diameter and choke size. … to optimize an objective function which is the present value of cumulative oil production.”, “developed IPR curves at any stage of depletion for solution gas-drive reservoirs using results obtained from a Black-Oil simulator. IPR curves are used here to optimize production parameters such as tubing diameter and choke sizes.”). In particular, Cadena et al. teaches a simple automatic procedure to generate IPR curves from reservoir simulators results and to use these IPR curves for production optimization (Abstract).
Guyaguler et al. and Cadena et al. are analogous art because they are both related to a method for reservoir simulation.
It would have obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to incorporate Cadena et al. into Guyaguler et al.’s invention for purpose of coupling reservoir and surface facility simulations to provide a simple automatic procedure can be developed to optimize production as the use of numerical simulators to represent reservoir behavior would require an excessive computational time (Cadena et al.: Abstract, Conclusion).
However, Guyaguler et al. as modified by Cadena et al. fails to teach explicitly a proxy.
Kohler et al. teaches as a proxy (Pg 1-3 section II, Fig. 2). In particular, Kohler et al. teaches SimProxy that can efficiently replace the use of commercial simulator in an optimization process, providing a good accuracy with a substantial decrease in computational cost (Pg 1, Abstract)
Guyaguler et al. as modified by Cadena et al. and Kohler et al. are analogous art because they are all related to a method for reservoir simulation.
It would have obvious to one having ordinary skill in the art to combine the teachings of Kohler et al. into Guyaguler et al. as modified by Cadena et al.’s invention to provide an accurate and, simultaneously, a computationally efficient integrated simulation, significantly improving the optimization process (Kohler et al.: left column on Pg 2).
As per Claim 2, Guyaguler et al. teaches wherein the at least one phase of fluid comprises a gas phase, an oil phase, a water phase, or any combination thereof (Col. 1 lines 24-43, “"reservoir simulations" refer to mathematical representations of fluid flow (e.g., oil, gas, water)”).
As per Claim 3, Guyaguler et al. fails to teach explicitly wherein the inflow performance relationship data for each well is generated as a function of cumulative production, as a function of cumulative injection, as a function of bottom hole pressure, as a function of tubing head pressure, or any combination thereof.
Cadena et al. teaches wherein the inflow performance relationship data for each well is generated as a function of cumulative production, as a function of cumulative injection, as a function of bottom hole pressure, as a function of tubing head pressure, or any combination thereof (left column on Pg 632, Equation (10)-(12)).
As per Claim 5, Guyaguler et al. teaches wherein the inflow performance relationship data is generated from a single physics-based subsurface-surface coupled simulation model (Fig. 1-3, Col. 9 lines 1-15, Col. 10 lines 31-40).
As per Claim 6, Guyaguler et al. teaches wherein the inflow performance relationship data is generated from multiple physics-based subsurface-surface coupled simulation models (Col. 13 lines 30-61).
As per Claim 13, Guyaguler et al. teaches further comprising computing a range of pressure points within the inflow performance relationship data for each well to generate the performance forecast (Col. 10 lines 60-65, Col. 11 lines 8-24).
As per Claim 14, Guyaguler et al. teaches wherein the surface simulator solves pressure and rate constraints of equipment on the surface during generation of the performance forecast (Col. 1 lines 24-43, Col. 9 lines 38-54).
As per Claim 15, Guyaguler et al. teaches wherein the surface simulator uses a surface network model to represent the surface during generation of the performance forecast (Col. 2 lines 3-25, Col. 8 lines 61-67, Col. 9 lines 1-5).
As per Claim 16, Guyaguler et al. fails to teach explicitly wherein the surface simulator uses a proxy to represent the surface during generation of the performance forecast.
Kohler et al. teaches wherein the surface simulator uses a proxy to represent the surface during generation of the performance forecast (Pg3-4, Fig. 4, section II.A).
As per Claim 17, Guyaguler et al. fails to teach explicitly wherein the proxy used by the surface simulator comprises a table lookup or a neural network.
Kohler et al. teaches wherein the proxy used by the surface simulator comprises a table lookup or a neural network (Pg 2-4 section II.A, Table 1, Fig. 4).
As per Claim 19-20, Guyaguler et al. taches a method/ computer system of generating a reservoir performance forecast (Title, Col. 9 lines 35-67, Col. 10 lines 1-30), the method comprising:
(Claim 20) one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions that when executed by the one or more processors cause the system (Title, Col. 9 lines 35-67, Col. 10 lines 1-30, Col. 12 lines 14-49) to:
a) initiating a full physics-based simulation using a subsurface simulator with a corresponding subsurface model representing a subsurface and one or more wells fluidly connecting to the subsurface (Col. 1 lines 24-43, Col. 8 lines 61-67, Col. 9 lines 1-5, “the use of external commercial surface facility network simulators… the reservoir can be modeled with a full-field commercial finite-difference reservoir simulator and the surface facilities can be modeled with a commercial non-transient network simulator”);
b) generating inflow performance relationship data for each well at each time step during the full physics-based subsurface simulation, wherein the inflow performance relationship data comprises performance data for at least one phase of fluid for each well (Col. 1 lines 24-43, Col. 6 lines 32-48, Col. 10 lines 60-67, Col. 11 lines 1-25, “"reservoir simulations" refer to mathematical representations of fluid flow (e.g., oil, gas, water)”, “A discretized IPR is generated for multiple pressure constraints in step 25. For steps 23,25, the sub-domain is solved with a timestep size … The sub-domain solve can be considered the same as creating a separate near-well model and then simulating this model with the appropriate boundary conditions. For example, for ten IPR points, ten sub-domain solves are carried out, which are equivalent to completing ten completely independent simulations on a small grid, but in the same process.”, “The IPR passed on to the surface facility network simulator typically includes a table with pressure (bottomhole or tubing head) and surface rates as columns. Each row in the table is a point on the IPRs at a particular pressure value.”: Examiner’s note – constructing an inflow performance relationship that reflects the near-well reservoir conditions at the endo f the timestep by solving each sub-domain repeatedly over the same timestep with different well constrains);
c) generating an inflow performance relationship database with the generated inflow performance relationship data for each well at each time step during the full physics-based subsurface simulation (Col. 9 lines 28-54, Col. 11 lines 1-25, “A discretized IPR is generated for multiple pressure constraints in step 25. For steps 23,25, the sub-domain is solved with a timestep size … The sub-domain solve can be considered the same as creating a separate near-well model and then simulating this model with the appropriate boundary conditions. For example, for ten IPR points, ten sub-domain solves are carried out, which are equivalent to completing ten completely independent simulations on a small grid, but in the same process.”, “The IPR passed on to the surface facility network simulator typically includes a table with pressure (bottomhole or tubing head) and surface rates as columns. Each row in the table is a point on the IPRs at a particular pressure value. ”: Examiner’s note - generating structured IPR table for each well at each coupling period.).
Guyaguler et al. fails to teach explicitly d) generating a reservoir performance forecast for a different simulation scenario using the subsurface simulator, wherein the subsurface simulator uses the inflow performance relationship database as a proxy to represent the subsurface in the different simulation scenario.
Cadena et al. teaches d) generating a reservoir performance forecast for a different simulation scenario using the subsurface simulator, wherein the subsurface simulator uses the inflow performance relationship database … to represent the subsurface in the different simulation scenario (right column on Pg 631 “One application of IPR is a production optimization method … to choose the best value of production parameters such as tubing diameter and choke size. … to optimize an objective function which is the present value of cumulative oil production.”, “developed IPR curves at any stage of depletion for solution gas-drive reservoirs using results obtained from a Black-Oil simulator. IPR curves are used here to optimize production parameters such as tubing diameter and choke sizes.”). In particular, Cadena et al. teaches a simple automatic procedure to generate IPR curves from reservoir simulators results and to use these IPR curves for production optimization (Abstract).
Guyaguler et al. and Cadena et al. are analogous art because they are both related to a method for reservoir simulation.
It would have obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to incorporate Cadena et al. into Guyaguler et al.’s invention for purpose of coupling reservoir and surface facility simulations to provide a simple automatic procedure can be developed to optimize production as the use of numerical simulators to represent reservoir behavior would require an excessive computational time (Cadena et al.: Abstract, Conclusion).
However, Guyaguler et al. as modified by Cadena et al. fails to teach explicitly as a proxy.
Kohler et al. teaches as a proxy (Pg 1-3 section II, Fig. 2). In particular, Kohler et al. teaches SimProxy that can efficiently replace the use of commercial simulator in an optimization process, providing a good accuracy with a substantial decrease in computational cost (Pg 1, Abstract)
Guyaguler et al. as modified by Cadena et al. and Kohler et al. are analogous art because they are all related to a method for reservoir simulation.
It would have obvious to one having ordinary skill in the art to combine the teachings of Kohler et al. into Guyaguler et al. as modified by Cadena et al’s invention to provide an accurate and, simultaneously, a computationally efficient integrated simulation, significantly improving the optimization process (Kohler et al.: left column on Pg 2).
5. Claims 4 and 7-12 are rejected under 35 U.S.C. 103 as being unpatentable over Guyaguler et al. (US 8805660 B2), in view of Kohler et al. (“SimProxy Decision Support System: A Neural Network Proxy Applied to Reservoir and Surface Integrated Optimization”) and Cadena et al. (“A Simple Procedure to Develop Analytical Curves of IPR from Reservoir Simulators with Application in Production Optimization”), and further in view of Liang et al. (“A Semi-Implicit Approach for Integrated Reservoir and Surface-Network Simulation”).
Guyaguler et al. as modified by Kohler et al. and Cadena et al. teaches most all the instant invention as applied to claims 1-3, 5-6, and 13-20 above.
As per Claim 4, Guyaguler et al. as modified by Kohler et al. and Cadena et al. fails to teach explicitly wherein the inflow performance relationship data for each well is generated using productivity index multiplier data in response to an acid treatment, a fracturing operation, formation damage, rock geomechanics, or any combination thereof.
Liang et al. teaches wherein the inflow performance relationship data for each well is generated using productivity index multiplier data in response to an acid treatment, a fracturing operation, formation damage, rock geomechanics, or any combination thereof (Equation (1)-(5) On the left column of pg 561, Appendix C).
Guyaguler et al. as modified by Cadena et al. and Kohler et al. and Liang et al. are analogous art because they are all related to a method for reservoir simulation.
It would have obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to combine the teachings of cited references. Thus, one of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to incorporate Cadena et al. into Guyaguler et al. as modified by Cadena et al. and Kohler et al.’s invention for purpose of coupling reservoir and surface facility simulations to provide a simple automatic procedure can be developed to optimize production as the use of numerical simulators to represent reservoir behavior would require an excessive computational time (Cadena et al.: Abstract, Conclusion), to provide an accurate and, simultaneously, a computationally efficient integrated simulation, significantly improving the optimization process (Kohler et al.: left column on Pg 2), and to provide a coupling technique with significant improvements surpassing explicit coupling in both stability and accuracy (Liang et al.: Abstract).
As per Claim 7, Guyaguler et al. as modified by Kohler et al. and Cadena et al. fails to teach explicitly wherein generating the reservoir performance forecast for the different simulation scenario comprises determining which inflow performance relationship from the inflow performance relationship database to utilize for each well at each prediction time-step based on the inflow performance relationship data.
Liang et al. teaches wherein generating the reservoir performance forecast for the different simulation scenario comprises determining which inflow performance relationship from the inflow performance relationship database to utilize for each well at each prediction time-step based on the inflow performance relationship data (section “Explicit and Semi-Implicit IPR” “IPR produced at the beginning of a timestep, time tn” on pg 560, Appendix C).
As per Claim 8, Guyaguler et al. as modified by Kohler et al. and Cadena et al. fails to teach explicitly further comprising… interpolation based on cumulative production, cumulative injection, or any combination thereof is utilized at each prediction time-step to determine which inflow performance relationship from the inflow performance relationship database to utilize for each well (Guyaguler et al.: Col. 9 lines 28-54, Col. 11 lines 1-25; Cadena et al.: Pg 632, Case 1, Pg 635 Fig. 5, Pg 638 Appendix B).
Guyaguler et al. as modified by Kohler et al. and Cadena et al. fails to teach explicitly using linear interpolation.
Liang et al. teaches further comprising using linear interpolation (Equation (8) on the right column of Pg 561).
As per Claim 9, Guyaguler et al. as modified by Kohler et al. and Cadena et al. teaches wherein the determined inflow performance relationships are truncated in response to flow constraints for each well (Guyaguler et al.: Col. 11 lines 8-25).
As per Claim 10, Guyaguler et al. as modified by Kohler et al. and Cadena et al. teaches wherein the flow constraints comprise bottom hole pressure, tubing head pressure, injection rate, production rate, or any combination thereof (Guyaguler et al.: Col. 9 lines 18-27, Col.10 lines 50-67).
As per Claim 11, as modified by Kohler et al. and Cadena et al. teaches wherein Kriging or a neural network based on cumulative production, cumulative injection, or any combination thereof from each well and its neighboring wells is utilized at each prediction time-step to determine which inflow performance relationship to utilize for each well (Kohler et al.: section 4)-5) on Pg 4-5 “Proxies Module”, Fig. 7).
As per Claim 12, as modified by Kohler et al. and Cadena et al. teaches wherein the neighboring wells are determined based on user specified criteria (Guyaguler et al.: Col. 7 lines 2-41).
Response to Arguments
6. Applicant's arguments filed on 01/07/2026 have been fully considered but they are not persuasive.
Examiner respectfully withdraws Claim Objections in view of the amendment and/or applicant’s arguments.
Examiner respectfully withdraws Claim Rejections - 35 USC § 101 in view of the amendment and/or applicant’s arguments.
Applicant’s arguments with respect to claim(s) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument - Guyaguler et al. (US 8805660 B2), in view of Kohler et al. (“SimProxy Decision Support System: A Neural Network Proxy Applied to Reservoir and Surface Integrated Optimization”), and further in view of Cadena et al. (“A Simple Procedure to Develop Analytical Curves of IPR from Reservoir Simulators with Application in Production Optimization”).
Conclusion
7. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ghorayeb; Kassem et al. (US 20070112547 A1)
8. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to EUNHEE KIM whose telephone number is (571)272-2164. The examiner can normally be reached Monday-Friday 9am-5pm ET.
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, Ryan Pitaro can be reached at (571)272-4071. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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EUNHEE KIM
Primary Examiner
Art Unit 2188
/EUNHEE KIM/Primary Examiner, Art Unit 2188
Prosecution Insights