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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Objections
Claim 1 is objected to because of the following informalities:
In claim 1 line 4, the acronym “AI” should be spelled out in its first instance.
In claim 1 lines 3, 6, and 10, it appears that “vibrating sensitivity-enhanced fiber optic cable” should be more clearly characterized as “vibration sensitivity-enhanced fiber optic cable.”
In claim 1 lines 7 and 8, it appears that “vibrating sensitivity-enhanced cladding” should be more clearly characterized as “vibration sensitivity-enhanced cladding.”
Appropriate correction is required.
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 1 is rejected under 35 U.S.C. 103 as being unpatentable over Bardainne (US 2021/0302609 A1) in view of Miller (US 2024/0184003 A1) and in further view of Hill (US 2012/0222487 A1) and Cai (CN109425451A).
As to claim 1, Bardainne teaches “[a] device for detecting and identifying shallow-stratum foreign objects (Abstract describing system for generating subsoil images; FIG. 2 system for recording seismic image information; [0049]-[0050] and [0052] system includes sensors deployed at relatively shallow subsoil positions; [0001]-[0002] and [0076] seismic analysis results in detecting subsoil structural anomalies (anomalous objects)) based on distributed acoustic sensing ([0050] system may implement distributed acoustic sensing (DAS)), comprising
a vibrating sensitivity-enhanced fiber optic” ([0050] system may implement fiber optic DAS, which entails a vibration/acoustically sensitive optical fiber line),”
“a vibrator system ([0010]-[0012]and [0035] overall system includes a source of seismic noise/vibration),
a vibration data processing unit ([0013]-[0015] and [0059]-[0060] system includes means for pre-processing seismic/vibration wave data; Abstract; [0012], [0018]-[0019], and [0069]-[0071] system includes means for implementing interferometry for ultimately rendering subsoil images from acoustic/seismic data),
a velocity structure inversion unit ([0028] and [0086] system includes inversion means for generating a wave speed/velocity model) and”
“wherein
the vibrating sensitivity-enhanced fiber optic cable is provided with a fiber core ([0050] system implements optical fiber DAS sensing. Examiner notes that optical fiber inherently includes a light-carrying core),”
“vibration data of the fiber optic” [fiber] is” “transmitted to the vibration data processing unit ([0013]-[0015] and [0059]-[0060] system includes means for pre-processing seismic/vibration wave data (data is received from optic fiber per [0050]; [0012], [0018]-[0019], and [0069]-[0071] system includes means for implementing interferometry for ultimately rendering subsoil images from acoustic/seismic data received from optic fiber per [0050]);
the vibration data processing unit is connected to the velocity structure inversion unit ([0022]-[0028] and [0086] reconstruction of data pre-processed per [0013]-[0015] and [0059]-[0060] and further processed per [0012], [0018]-[0019], and [0069]-[0071] is implemented by subsequent inversion (requires data connectivity between the vibration data processing means and inversion means)).”
Bardainne does not explicitly describe the optical fiber as being part of a “cable.” Housing optical fiber used for DAS as part of a “cable” was well known prior to the effective filing date. For example, Miller discloses a system for implementing distributed subsurface imaging (Abstract) that may be implemented using DAS ([0024] and [0027]) including fiber optic cables ([0044]-[0045]).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Miller’s teaching of using fiber optic cables for DAS imaging to the device taught by Bardainne such that Bardainne’s optical fibers are deployed as fiber optic cables.
Such a combination would amount to selecting a known design option for deploying fiber optic sensors to achieve predictable results.
Regarding the device including “a distributed acoustic sensing demodulator,” and “the vibrating sensitivity-enhanced fiber optic cable is connected to the distributed acoustic sensing demodulator,” and vibration data of the fiber optic cable is “acquired through the distributed acoustic sensing demodulator,” Bardainne’s discloses use of processing fiber optic signals at least suggests that demodulation of the optical signals (Abstract; [0012], [0018]-[0019], and [0069]-[0071] system that per [0050] may be fiber optic DAS, renders subsoil images from acoustic/seismic data interferometry to generate seismogram (demodulate/decodes the acoustic data from the optical fiber).
Furthermore, Miller discloses demodulation of DAS optical sensing signals acquired by a demodulation function ([0044] DAS sensing includes processing of optical energy received from fiber optical cables, such as by an interrogator, to measure interference in standing waves to sensing changes in density (reflecting strain) (i.e., demodulation of optical energy) to perform interferometry).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Miller’s teaching of the need for demodulation of the optical signals/energy for interferometry to the device taught by Bardainne as modified by Miller such that in combination the device includes a distributed acoustic sensing demodulator that is connected to the vibrating sensitivity-enhanced fiber optic cable to initially acquire the vibration data from the fiber optic cable.
Such a combination would amount to selecting a known (and standard) design option for implementing DAS sensing to achieve predictable results.
Bardainne does not teach “an AI-aided locating and identification unit” “connected to the vibration data processing unit and the velocity structure inversion unit.”
Miller further teaches that the subsurface imaging system includes an AI-aided locating and identification unit (FIG. 2 computing system 224 including machine learning model 204, [0034] machine learning model receives/processes acoustic data and external data to generate imaging of subsurface objects including location and form of objects) that is connected to a vibration data processing unit (FIG. 2 machine learning model 204 receives input from (connected to) acoustic data 220 and external data 223, [0032] external data may be DAS sensor data (data processed by DAS), [0044]-[0045] acoustic data obtained from DAS).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Miller’s teaching of using an AI-aided unit connected to acoustic/vibration processing sources to the device taught by Bardainne in which acoustic imaging data is generating via processing unit and inversion unit (following initial processing) such that in combination the device is configured to include “an AI-aided locating and identification unit” “connected to the vibration data processing unit and the velocity structure inversion unit.”
The motivation would have been to leverage the learning and multivariate data processing capability of AI to optimize subsurface object imaging as disclosed by Miller.
Each of Bardainne and Miller are largely silent regarding the structure of the fiber optic cable used for DAS and therefore neither teaches “the fiber core is wrapped by a vibrating sensitivity-enhanced cladding, a vibrating low-loss Bingham body filling gel is filled between the vibrating sensitivity-enhanced cladding and a jacket, and cable-soil coupling-enhanced fins are additionally arranged on the jacket.”
Hill discloses a system for distributed fiber optic sensing (Abstract) in which a fiber optic cable deployed for DAS ([0033]; FIG. 1 depicted DAS functionality) including for subsurface imaging ([0068]) and in which the cable includes a fiber core wrapped by a vibrating sensitivity-enhanced cladding (FIG. 2a optical fiber cable 201 including core 208 enclosed/wrapped by a cladding 206 (for DAS application would constitute cladding suitable/enhanced for vibration measurement)), and in which a vibrating low-loss filling gel is filled between the vibrating sensitivity-enhanced cladding and a jacket (FIG. 2A optical fiber cable 201 includes buffer material 202 disposed between cladding 206 and jacket 204, [0075]; [0032]-[0033] buffer material may be a gel that enhanced vibration/acoustic sensitivity. Examiner notes that “gel” itself constitutes a low-loss substance in terms of being substantially solid (gel). Examiner further notes that the improved/enhanced sensitivity qualifies the gel as low-loss and applies to the overall structure including the cladding with which the gel is in contact.)
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Hill’s teaching of a DAS sensing/imaging system in which the cable includes a fiber core wrapped by a vibrating sensitivity-enhanced cladding, and in which a vibrating low-loss Bingham body material (e.g., a gel) is filled between the vibrating sensitivity-enhanced cladding and a jacket.
Using sensitivity enhanced cladding surrounding the fiber core would amount to selecting a known design option for implementing fiber optic acoustic sensing cables to achieve predictable results. The motivation for disposing a gel between the cladding and a jacket would have been to improve acoustic sensitivity as disclosed by Hill.
Hill is silent regarding the type of gel and therefore does not teach that the gel is a “Bingham body” gel. Bingham substances are characterized by the viscoplastic property of maintaining solidity (gel state) until a yield force is applied causing the gel to transform to liquid during application of the force and return to solid/gel state upon removal of the force. Hill’s implementation appears to suggest desirability of maintaining some level of rigidity in the otherwise flexible cable (FIG. 1 depicting malleable deployment (requiring application of force) of sensing fiber 104; [0080] describing embodiment in which extra rigidity implemented using a solid material). Furthermore, Hill notes that acoustic transmission sensitivity is an important property of the gel [0081], which would be recognized by one of ordinary skill in the art as reliant on minimally disrupted material/acoustic interfaces such that in Hill’s depicted embodiment (e.g., FIGS. 1 and 2a-2B in which cable is malleably disposed such that the positioning of the core/cladding unit 208/206 is subject to shifting retention within buffer material). It would therefore have been obvious to one of ordinary skill in the art prior to the effective filing date to have uses a Bingham type gel (gel having transitioning between solid and liquid depending on application of force) as the gel used as a buffer material between the cladding and outer jacket.
The motivation would have been the benefit of using a gel as suggested by Hill having such properties in terms of retaining the fiber core substantially in a fixed position while permitting relative flexure/motion of the fiber core and further enables the gel to interact fluidly with the core/cladding unit during application of bending force to prevent fracturing of the gel substance to maintain optimal acoustic transmission.
None of Bardainne, Miller, and Hill teach “cable-soil coupling-enhanced fins are additionally arranged on the jacket.”
Cai discloses an apparatus for implementing fiber optic soil monitoring (Abstract) in which soil coupling fins are arranged on an outer surface of a fiber optic cable (Abstract describing soil body monitoring device to be buried in soil, and which includes fins arranged “on” a fiber optic cable; FIG. 1 depicting fiber optic cable 1 and positioning plates 31 arranged via joint on the outer surface of cable 1.
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Cai’s teaching of arranging soil coupling fins on the exterior of a fiber optic cable to the device taught by Bardainne as modified by Miller and Hill, such that in combination the DAS implemented fiber optic cable includes cable-soil coupling-enhanced fins arranged on the jacket.
The motivation would have been to position stabilize the fiber optical cable with respect to the ground/soil position to protect accuracy of corresponding location-based measurements as suggested by Cai.
Allowable Subject Matter
Claims 2-10 are objected to as being dependent upon a rejected base claim but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is an examiner’s statement of reasons for allowance:
Regarding claim 2, the most pertinent prior arts are represented by Bardainne (US 2021/0302609 A1), Miller (US 2024/0184003 A1), Hill (US 2012/0222487 A1), Cai (CN109425451A), and Noetzli (US 2025/0277693 A1).
As to claim 2, the combination of Bardainne, Miller, Hill, and Cai teaches “[a] method for detecting and identifying shallow-stratum foreign objects (Bardainne: Abstract describing system implementing method for generating subsoil images; FIG. 2 system implementing method for recording seismic image information; [0049]-[0050] and [0052] system includes sensors deployed at relatively shallow subsoil positions; [0001]-[0002] and [0076] seismic analysis results in detecting subsoil structural anomalies (anomalous objects)) based on distributed acoustic sensing ([0050] system/method may implement distributed acoustic sensing (DAS)), implemented by the device for detecting and identifying shallow-stratum foreign objects based on distributed acoustic sensing according to claim 1 (as set forth in the grounds for rejecting claim 1), wherein the method comprises following steps:
(1) wrapping the vibrating sensitivity-enhanced cladding outside the fiber core (Hill: FIG. 2a cladding 206 wrapped outside fiber core 208), filling the vibrating low-loss Bingham body filling gel between the vibrating sensitivity-enhanced cladding and the jacket (Hill: FIG. 2A optical fiber cable 201 includes buffer material 202 disposed between cladding 206 and jacket 204, [0075]; [0032]-[0033] buffer material may be a gel that enhanced vibration/acoustic sensitivity. As combined with Hill for claim 1 constitutes a Bingham body gel), and additionally arranging the cable-soil coupling-enhanced fins on the jacket (as combined with Cai for claim 1 includes cable-soil coupling-enhanced fins on the jacket), to make the vibrating sensitivity-enhanced fiber optic cable (Bardainne and Miller as combined with Hill and Cai for claim 1);
(2) shallowly burying the vibrating sensitivity-enhanced fiber optic cable in a shallow-stratum detection area (Bardainne: [0049]-[0050] and [0052] system includes sensors deployed at relatively shallow subsoil positions),”
“(3) connecting the vibrating sensitivity-enhanced fiber optic cable to the distributed acoustic sensing demodulator (Bardainne as combined with Miller for claim 1), and setting sampling parameters of the distributed acoustic sensing demodulator (sampling is an inherent and necessary feature of demodulation);
(4) transmitting active vibrator signals through the vibrator system (Bardainne: [0010]-[0012]and [0035] overall system includes a source of seismic noise/vibration), and acquiring vibration data of the vibrating sensitivity-enhanced fiber optic cable in a set time period through the distributed acoustic sensing demodulator (Bardainne: FIG. 1 block 10 seismic waves recorded/received. As described with reference to Bardainne (e.g., [0012] and [0054]-[0054] system implements acoustic monitoring over vibration source activity that would occur over time);
(5) transmitting the vibration data acquired through the distributed acoustic sensing demodulator to the vibration data processing unit (Bardainne: ([0013]-[0015] and [0059]-[0060] system includes means for pre-processing seismic/vibration wave data (data is received from optic fiber per [0050]; [0012], [0018]-[0019], and [0069]-[0071] system includes means for implementing interferometry for ultimately rendering subsoil images from acoustic/seismic data received from optic fiber per [0050]), preprocessing the vibration data through the vibration data processing unit (Bardainne: [0013]-[0015] and [0059]-[0060] system includes means for pre-processing seismic/vibration wave data; Abstract; [0012], [0018]-[0019], and [0069]-[0071] system includes means for implementing interferometry for ultimately rendering subsoil images from acoustic/seismic data), displaying waveform changes of vibration signals in the fiber optic cable over time (Bardainne: [0087] subsoil image is generated over time in an evolutionary manner), and identifying a fiber optic cable channel (Bardainne: [0062] signal filtered within a predetermined band of frequencies which corresponds to both the estimated emission band of the vibration source and to the frequency band of interest (channel), which depends on the depth of interest of the investigation of the subsoil under the target zone) where a shallow-stratum foreign object is located according to abnormal waveforms (Bardainne: [0001]-[0002] and [0076] seismic analysis results in detecting subsoil structural anomalies (anomalous objects)), so that a plane position of an underground foreign object is determined (Miller (as combined with Bardainne for claim 1): FIG. 2 computing system 224 including machine learning model 204, [0034] machine learning model receives/processes acoustic data and external data to generate imaging of subsurface objects including location and form of objects);
(6) transmitting the preprocessed vibration signals to the velocity structure inversion unit through the vibration data processing unit (Bardainne: [0022]-[0028] and [0086] reconstruction of data pre-processed per [0013]-[0015] and [0059]-[0060] and further processed per [0012], [0018]-[0019], and [0069]-[0071] is implemented by subsequent inversion (requires data connectivity between the vibration data processing means and inversion means)), performing inversion of a shallow-stratum underground velocity structure to obtain a shallow-stratum underground velocity structure of the detection area (Bardainne: [0028] and [0086] system includes inversion means for generating a wave speed/velocity model), and analyzing a ground depth of the shallow-stratum foreign object according to an abnormal shear wave velocity, so as to determine three-dimensional coordinates of the shallow-stratum foreign object (Bardainne: [0062] signal filtered within a predetermined band of frequencies which corresponds to both the estimated emission band of the vibration source and to the frequency band of interest, which depends on the depth of interest of the investigation of the subsoil under the target zone(sone of prospective anomalies); [0086] acoustic waves may be shear waves); and
(7) receiving data images from the vibration data processing unit and the velocity structure inversion unit through the AI-aided locating and identification unit (Miller as combined with Bardainne for claim 1), denoising” “data images (Bardainne: [0060]-[0061] imaging data is denoised),” “performing binary” “segmentation on the generated denoised images (Bardainne: [0063] and [0065] binarization performed on denoised signal),”
“by use of a” “learning algorithm (Miller as combined with Bardainne for claim 1 teaching use of machine learning model).”
Miller further teaches that the machine learning model may be a deep learning model ([0038]) that is trained for target detection ([0036]-[0038]) and Bardainne further teaches that the acoustic data includes contours and elastic wave response characteristics ([0086] produce a speed model of the pressure and shear waves (inherently entails contours and elastic wave response characteristics)) for different shallow-stratum foreign objects ([0001]-[0002] and [0076]).
It would have been obvious to one of ordinary skill in the art before the effective filing date, to have applied Miller’s teaching of using a deep learning model trained for target detection to the method taught by Bardainne as modified by Miller, Hill, and Cai, which teaches that the acoustic data includes contours and elastic wave response characteristics for different shallow-stratum foreign objects such that in combination the method includes use of a deep learning algorithm, training a deep learning model for target detection according to contours and elastic wave response characteristics of different shallow-stratum foreign objects, and identifying types of the shallow-stratum foreign objects.
Such a combination would amount to combining known seismic imaging elements in known ways to achieve predictable results.
Regarding “inspecting circuit integrity and cable-soil coupling of the vibrating sensitivity-enhanced fiber optic cable” Cai teaches a form of inherent fiber optic cable inspection in terms of installing the cable that per Cai includes cable-soil coupling entails a form of inspection. Furthermore, Noetzli discloses a system for implementing DAS monitoring for target equipment in which the target equipment is inspected for correct operation ([0136], [0169], and [0195]).
It would have been obvious to one of ordinary skill in the art before the filing date, to have applied Noetzli’s generalized teaching of the utility of inspecting equipment and Cai’s teaching of coil-coupling installation to the method taught by Bardainne as modified by Miller, Hill, and Cai, such that the method includes extended inspection to electronic/circuit functions of the DAS device as well as the coil-coupling aspects of the cable apparatus.
The motivation would have been to ensure optimal operation of the overall equipment as suggested by Noetzli.
The prior arts do not appear to fairly teach or suggest the combined process of “denoising the data images through a shallow-stratum foreign object image denoising method” in which per antecedent relation “the data images” are post-inversion processing data images, and “performing binary semantic segmentation on the generated denoised images, and separating the shallow-stratum foreign object along its boundary according to a background of the denoised images” in combination with the other elements of claim 2 including the limitations of claim 1 from which claim 2 depends.
Claims 3-10 depend from claim 2 and are likewise allowable over the prior arts for the same reasons.
Conclusion
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/MATTHEW W. BACA/Examiner, Art Unit 2857
/ANDREW SCHECHTER/Supervisory Patent Examiner, Art Unit 2857
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