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 .
Response to Amendment
Applicant’s argument regarding neither in combination nor individually cited prior arts of record Karimi et al. and Camacho et al. teach the details of wherein at least a first KPI score is determined from the at least first KPI data and is normalized using a predetermined normalization procedure, and at least a second KPI score is determined from the at least second KPI data and is not normalized has been fully considered but in moot in view of newly cited reference Flockhart et al. in combination with previously cited prior arts of record. Flockhart et al. explicitly teaches in [0050], [0007], [0069] and [0070] that a subset of KPIs for certian goals and rules are selected where some of the selected KPIs are normalized and rest of them are not normalized. Using the combination of normalized and not normalized KPIs, a work decision is made that is similar to claimed rig efficiency index. Therefore it would have been obvious before the effective filing date of the claimed invention to a person of ordinary skill in the art to modify the system calculating a rig efficiency index from plurality of KPI scores as taught by combination of Karimi et al. and Camacho et al. by applying the known technique of using a combination of normalized KPIs and not normalized KPIs to determine a decision as taught by Flockhart et al. as an improvement to efficiency calculation to yield predictable results for accurately determining equipment/rig health by weighing in all the KPIs with appropriate importance as taught by Flockhart et al. in [0069].
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) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Karimi et al. (US 20190292908 A1) in view of Camacho et al. (US 20190264545 A1) and Flockhart et al. (US 20130083916 A1).
Regarding claim 1, Karimi et al. teaches, an input device configured to receive at least a first and second key performance indicator (KPI) data of at least one rig among a set of rigs, wherein each of at least first and second KPI data is selected from the group consisting of: flat time performance data, rig lost time performance data, and health-safety-environment data (Fig 1,para [0038]: "to identify D&C performance indicators" and para [0039]: "conduct automated quality control (QC) and information mining for large data sets associated with daily drilling and completions reports, aggregate data sets from different sources1, predict the productive and non-productive time at the hydrocarbon extraction site 118 and its type, predict the drilling phase (drilling ahead, pulling out of the hole, casing and cement, installing a blow-out preventer (BOP), logging etc.), identify drilling bottlenecks, conduct detailed analysis by using metrics which tie D&C to production, geology, and reservoir management, assign a global drilling and completion score to a well which considers parameters such as wellbore placement, days to drill and complete, hydrocarbon production rate, cost, rate of penetration, etc., and apply this data driven approach and historical data associated with this method for more accurate production forecast for future planning and resource allocation"; see also para [0104]:data of environment 100" & para [0098]: "A score is obtained for each Key Performance Indicator (KPI)" and para [0107]);
a processor configured by code executing therein to calculate a plurality of
KPI scores from the KPI data, and to calculate a rig efficiency index (REI) from the
plurality of KPI scores (para [0098]: "A score is obtained for each Key Performance
Indicator (KPI) ... The Global drilling score may be obtained as the weighted average of
each KPI score [i.e., each of plurality of KPI]. The weight for each KPI may vary for each
application," para [0042]: "A global scoring system [i.e., global drilling score] is provided
herein to identify the problems associated with each well, as well as proposed solutions.
Eventually, these analyses are used to optimize future planning and resource allocation
at the hydrocarbon extraction site/region 118, and to maximize production/or NPV and
improve capital efficiency" & para [0051]: "One other possibility is to correlate the daily
production data with drilling and completion performance [i.e., global drilling score] by
using the drilling efficiency index (DEi) and completion efficiency index (CEI)"; see also
paras [0082] - [0085] & para [0089]: "global drilling score might show that DEi" & [0090]
- [0094]);
a rig controller configured by code executing therein and responsive to the
case that the REI (drilling inefficiency index) is less than a predetermined threshold to generate and output a control signal based on the REI (paras [0082] - [0085] & para [0110] - [0111]: "The inefficiencies 115 may identify any individual piece of D&C equipment 119 that is operating at a pace or level (drilling inefficiency index) that is below what is possible [i.e., predetermined threshold] ... upon identifying the at least one drilling and completion inefficiency 115, performing at least one remediation step 117 to resolve the at least one identified inefficiency (1460)"; see also paras [0124] - [0125]: "In some cases, the objective function may be ... to minimize the operation time. In any case [i.e., the case that the REI is less than a predetermined threshold], inefficiencies 115 will be reduced and production will be increased. Once the rig scheduling sequence 132 has been generated, the extraction rig 121 may be operated according to the optimized rig scheduling sequence").
Karimi et al. does not explicitly teach the details of a connection connecting the
rig controller to at least a first rig among the set of rigs, and configured to convey the
control signal from the rig controller to the first rig among the set of rigs to control the
first rig by changing a state of operation of the first rig and wherein at least a first KPI score is determined from the at least first KPI data and is normalized using a predetermined normalization procedure, and at least a second KPI score is determined from the at least second KPI data and is not normalized. However Karimi et al. explicitly
teaches in paras [0110]-[0111] a remediation module can take necessary steps to return
the equipment or rig 121 to its higher level of efficiency based on the KPI and the REI.
But is not clear whether the equipment is another rig or whether the remediation module
is sending signal to a particular rig of rig 121 which can include multiple rigs as per para
[0053].
Camacho et al. teaches, a connection connecting the rig controller to at least a first rig among the set of rigs (rig among the one of the multiple drilling rig sites, [0020]), and configured to convey the control signal from the rig controller (health management system determining and monitoring health of plurality of rig equipment of all drilling rig systems at multiple drilling sites, [0020] and [0027]) to the first rig among the set of rigs to control the first rig by changing a state of operation of the first rig (a health management system monitoring rigs located at multiple drilling sites and present the individual rig health index in a HMI as taught in [0020] and [0033]. When one of the rig's health index is reaching upper or lower limit, the health management system can automatically change the corresponding rig usage to avoid damage of the rig equipment as taught in [0020] and [0027]. The health management system communicates with the rigs in the drilling rig sites using communication circuit as taught in [0033], which connects the rigs to a network where
the health management system is also connected, [0027], [0032], [0033] and [0035]).
Therefore it would have been obvious before the effective filing date of the
claimed invention to a person of ordinary skill in the art to modify the system calculating
rig efficiency index from the plurality of KPI scores for at least one rig among set of rigs
and generate a control signal based on the calculated REI less than a predetermined
threshold as taught by Karimi et al. by connecting the rig controller to at least first rig
among the set of rigs to convey the control signal as taught by Camacho et al. as an
improvement to rig operation to yield predictable results for effectively monitoring and
controlling multiple rigs.
Neither in combination nor individually Karimi et al. and Camacho et al. teach the details of at least a first KPI score is determined from the at least first KPI data and is normalized using a predetermined normalization procedure, and at least a second KPI score is determined from the at least second KPI data and is not normalized. However Karimi et al. teaches in [0109] that a large amount of current and past data for a given rig or piece of equipment is used to determine plurality of KPI scores as taught in [0098] which are then weighted to deter global drilling inefficiency index for a rig/equipment. It is not clear whether the all the datasets involved in calculation uses normalized and not normalized data. On the other hand Flockhart et al. teaches, wherein at least a first KPI score is determined from the at least first KPI data and is normalized using a predetermined normalization procedure (the analytics engine normalizes some of the selected KPIs, [0050],[0069] and [0070]), and at least a second KPI score is determined from the at least second KPI data and is not normalized (the analytics engine normalizes some of the selected KPIs and leaves rest of the KPIs unprocessed that is not normalized. All the selected KPIs2 (both normalized and not normalized) are used to make a decision about the work assignment that is composite score determined based on the all the normalized and not normalized KPIs, [0050], [0069] and [0070]).
Therefore it would have been obvious before the effective filing date of the claimed invention to a person of ordinary skill in the art to modify the system calculating a rig efficiency index from plurality of KPI scores as taught by combination of Karimi et al. and Camacho et al. by applying the known technique of using a combination of normalized KPIs and not normalized KPIs to determine a decision as taught by Flockhart et al. as an improvement to efficiency calculation to yield predictable results for accurately determining equipment/rig health by weighing in all the KPIs with appropriate importance as taught by Flockhart et al. in [0069].
Flockhart et al. teach:
[0069] In some embodiments, the analytics engine 124 may optionally normalize the KPI(s) before providing the KPI(s) to the work assignment engine 120 (step420). Specifically, the analytics engine 124 may be configured to determine how far away each selected KPI is from the goal for that KPI (e.g., as an absolute value or +/-a certain amount). The analytics engine 124 may calculate the normalized KPI in any number of ways. As one example, the analytics engine 124may determine the difference between the current KPI value and the goal for that KPI value and then divide the difference by the goal for the KPI value. Normalization may be particularly useful in situations where the analytics engine124 selects a plurality of KPIs, as the normalization may help reduce the importance of one KPI as compared to another KPI. However, it may also be possible to normalize KPIs so as to emphasize certain KPIs relative to other KPIs.
[0070] The selected KPI value(s), whether normalized or not3, may then be provided from the analytics engine 124 to the work assignment engine 120 as matching parameters (step 424).
[0050] In some embodiments, the KPIs that are retrieved at the data connector136 and provided to the analytics engine 124 describe the current operating conditions of the contact center. The analytics engine 124 may utilize the inputs and one or more business rules 126 that define desired operating goals of the contact center to select one or more real-time KPIs. The selected one or more KPIs (e.g., a subset of the KPIs received from the data connector 136) may then be provided to the work assignment engine 120. The work assignment engine 120can then utilize the KPIs received from the analytics engine 124 and the bitmaps/tables 128 to make a work item assignment decision.4 In particular, the work assignment engine 120 may use the KPIs received from the analytics engine124 as routing parameters. The KPIs, as routing parameters, can be used to build one or more bitmaps/tables 128 that will eventually cause a work item to be assigned to a resource 112.
Regarding claim 2 combination of Karimi et al., Camacho et al. and Flockhart et al. teach the system of claim 1. In addition Karimi et al. teaches, wherein the processor calculates the REI from a weighting of the plurality of KPI scores (calculating KPls for the monitored rigs, [0098]-[0100]).
Regarding claim 3 combination of Karimi et al., Camacho et al. and Flockhart et al. teach the system of claim 1. In addition Camacho et al. teaches, wherein the connection is a communication line connecting the rig controller to at least the first rig (the health management system can alter the operation of one of the monitored rig by sending signals using the communication network, [0020],[0033] and [0035]).
Regarding claim 4 combination of Karimi et al., Camacho et al. and Flockhart et al. teach the system of claim 1. In addition Karimi et al. teaches, wherein the set of rigs includes a plurality of rigs (scheduling plurality of rigs, [0099] and [0100]), and
wherein the processor calculates at least one of the plurality of KPI scores
as an aggregated score of the plurality of rigs (calculating KPI scores for plurality of
monitored rigs, [0098]-[0100]).
Regarding claim 5 combination of Karimi et al., Camacho et al. and Flockhart et al. teach the system of claim 1. In addition Karimi et al. teaches, wherein the rig controller controls the first rig when the REI is less than the predetermined threshold5 (when the net productive value is below a productivity level (predetermined value), an optimized schedule is determined to increase rig operation efficiency, [0124]-[0125] and [0098]-[0100]).
Regarding claim 6 combination of Karimi et al., Camacho et al. and Flockhart et al. teach the system of claim 1. In addition Camacho et al. teaches, wherein the changing of the state of operation of the first rig is selected from the group consisting of: re-bid the first rig, re-contract the first rig, release the first rig, and shut down the first rig (based on the health index of the rig at threshold value, the health management system can trigger appropriate actions such as reduce/stop using the plurality of rigs, optimize operation schedule of the rigs (in view of Karimi et al.),maintain status quota, etc., [0020] and [0023]).
Regarding claim 7 combination of Karimi et al., Camacho et al. and Flockhart et al. teach the system of claim 1. In addition Karimi et al. teaches, further comprising: an output device configured to output the REI associated with the at least one rig (the NPT value, DEi, CEI, KPI values are calculated for each of the rigs monitored, [0082]-[0085] and [0098]-[0100]).
Regarding claim 9 combination of Karimi et al., Camacho et al. and Flockhart et al. teach the claimed system controlling the first rig by changing a state of operation of the first rig. Therefore together they teach the system implementing the functional steps of controlling the first rig operation as taught in claim 1.
Regarding claims 10-15 combination of Karimi et al., Camacho et al. and Flockhart et al. teach the claimed system controlling the first rig by changing a state of operation of the first rig. Therefore together they teach the system implementing the functional steps of controlling the first rig operation as taught in claims 2-7.
Regarding claim 16 combination of Karimi et al., Camacho et al. and Flockhart et al. teach the claimed system controlling the first rig by changing a state of operation of the first rig. Therefore together they teach the method implementing the functional steps of controlling the first rig operation as taught in claim 1.
Regarding claims 17-20 combination of Karimi et al., Camacho et al. and Flockhart et al. teach the claimed system controlling the first rig by changing a state of operation of the first rig. Therefore together they teach the method implementing the functional steps of controlling the first rig operation as taught in claims 2,5,6 and 7.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Hnich et al. (US 20220004969 A1) teaches a system and method for providing knowledge base to learners based of KPIs calculated using both normalized score and non-normalized scores.
Vitullo et al. (US 20230047122 A1) teaches a combination of datasets is used to determine stability index for an equipment to indicate its current health condition. In the combination of datasets, some datasets include unprocessed operational data that is non-normalized data as taught in [0081] and some datasets include preprocessed data that is normalized operational data as taught in [0082] and [0003]. Combination of the above datasets are used to perform several analyses (KPIs are calculated) to determine the stability index (calculated based on analyses result) which is similar to the claimed efficiency index calculated based of plurality of datasets where one dataset is normalized and another one (dataset) is not normalized, [0081]-[0083]).
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANZUMAN SHARMIN whose telephone number is (571)272-7365. The examiner can normally be reached M and Th 7:00am - 3:00pm and Tue 8:00am-12:00pm.
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/ANZUMAN SHARMIN/Examiner, Art Unit 2115
/VINCENT H TRAN/Primary Examiner, Art Unit 2115
1 Different datasets for calculating score of the KPI.
2 Either normalize all the KPIs or normalize some KPIs only, both of the these are obvious variations of each other since Flockhart et al. mentioned in [0069] that normalization may reduce the importance of one KPI comparted to other KPIs. Because if one KPI is always large compared to the other KPIs, when added togather or compared together one KPI will always be dominant than rest of the KPIs leading to a wrong or false calculation. That is why is it important to normalize the KPI with bigger scale to match the KPI in the smaller scale. KPIs on the smaller scale does not require normalization during comparison or addition since the original values already reflect the current condition accurately compared to other bigger scale KPIs.
3 That is combination of normalized and not normalized KPIs (see [0007]) used for making a decision for a work assignment as taught in [0050].
4 Composite KPIs added to determine a decision.
5 In view of [0032] of Camacho et al., when the health index value is at the threshold, the health
management system can automatically change the usage of the plurality of rig equipment. Seel also [0082] and [0083] of Vitullo et al. where the stability index is below a threshold.
Prosecution Insights