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 Arguments
Claims 1-8, 10, 11, 14, 15, 17, 19-21, 41, 61, and 62 are pending, independent claim 1 and dependent claims 5, 6, 8, and 20 are amended, dependent claims 61 and 62 are new, and claims 9, 16, and 18 are cancelled.
With regards to the new dependent claims 61 and 62, a new ground(s) of rejection is made in view of U.S.C 112(a) and U.S.C. 112(b).
New grounds of rejections of U.S.
Applicant’s arguments on page 8, filed 10/10/2025, with respect to the Objection in the specification has been fully considered and are persuasive. The Objection in the specification has been withdrawn.
Applicant’s arguments on pages 8-14, filed 10/10/2025 with respect to U.S.C. 101 rejection of claims 1-8, 10, 11, 14, 15, 17, 19-21, 41, 61, and 62 have been fully considered and are persuasive. The U.S.C. 101 rejections of claims 1-8, 10, 11, 14, 15, 17, 19-21, 41, 61, and 62 have been withdrawn.
Applicant’s arguments, see page 14, filed 10/10/2025, with respect to the rejection(s) of claim(s) 1-5, 7-10, 14, 15, 17-19, 21, and 41 under U.S.C. 102 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of U.S.C. 103.
Applicant argues that Pop do not teach all the limitations of the claims 1-5, 7-10, 14, 15, 17-19, 21, and 41, because of the newly amended limitations in claim 1. Examiner agrees, however with the newly amended limitations in claim 1, previously used art Venkataramanan et al. (US 20170241922 A1) hereinafter Venkataramanan has also been used and examiner directs the applicant to the rejection below.
Applicant’s arguments, see page 15, filed 10/10/2025, with respect to the rejection(s) of claim(s) 6 and 11 under U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of U.S.C. 103.
Applicant argues that Pop in view of Proett or Osborne does not teach all the limitations of the claims 6 and 11 because of the newly amended limitations in claim 1. Examiner agrees, however with the newly amended limitations in claim 1, previously used art Venkataramanan et al. (US 20170241922 A1) hereinafter Venkataramanan has also been used and examiner directs the applicant to the rejection below.
Applicant’s arguments, see page 15-20, filed 10/10/2025, with respect to the rejection(s) of claim 16 now newly amended limitation of claim 1, and claim 20 under U.S.C. 103 have been fully considered and are not persuasive.
Applicant argues that Venkataramanan relates exclusively to the analysis and interpretation of nuclear magnetic resonance (NMR) relaxation data, and does not address formation-tester contamination, contamination cleanup as a function of time or pumpout volume, or the prediction of cleanup targets in the context of formation sampling, therefore its use of the mathematical idea of utilizing a sum of exponential decays cannot be applied to Pop to cover the limitation “decomposes the level of contamination as a sum of a plurality of exponential decays and determines [s] formation condition based on the decomposition.”
Examiner respectfully disagrees. Pop discusses how contamination can be written as a mathematical function of time of volume of the fluid pumped from the formation in [0099]. Venkataramanan is found to discuss the use of the sum of exponential equations during the use of NMR relaxation, a type of formation test tool analysis that is commonly utilized in borehole formation and drilling. Thus, the use of the mathematical principle of using the sum of exponential equations a commonly understood principle in the art, and to one of ordinary skill. There is no limitation that indicating that the type of formation test tool utilized to analyze a sample in the operation cannot be NMR or NMR related. Furthermore, there is no limitation stating that the numerical model that decomposes into a plurality of exponential decays is not NMR relaxation, as NMR relaxation is also a function of time. Limitations that are not claimed are not addressed by the rejection. For at least these reasons, Applicant’s argument is unpersuasive.
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.
Claim 61 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 61 recites “regularized exponential decomposition” in line 2. It is unclear what the applicant means by the term “regularized”. For the purpose of examination the term regularized exponential decomposition will be interpreted to mean taking a curve on the graph and finding the exponential decay of the curve.
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) 1-5, 7, 8, 10, 14, 15, 17, 18, 19-21, 41, and 61 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pop et al. (US 20150330218 A1) hereinafter Pop in view of Venkataramanan et al. (US 20170241922 A1) hereinafter Venkataramanan.
Regarding Claim 1, Pop teaches using a formation testing tool to obtain a sampled fluid from a formation according to a set of sampling parameters ([0073] “Such gathered data may include parameters measured by, for example, LWD or MWD tools (i.e., formation tools). In particular, drilling fluid parameters, borehole temperatures and pressures, borehole geometries, trajectory, etc., formation properties, formation fluid properties (e.g., collected during one or more sampling operations (e.g., during one or more preliminary tests) while the drilling is temporarily stopped), etc. may be measured and gathered for a pre-determined period of time or, alternatively, until a predetermined condition or set of conditions is/are satisfied ( e.g., a particular depth has been reached, one or more measured parameter values are within a certain target range of values, above or below a threshold value, etc.).”); using the formation testing tool to analyze the sampled fluid to identify a set of fluid parameters for the sampled fluid ([0087] “the identified possible scenarios, plans or processes and the related parameters and parameter values are processed by the simulation engine 240 and/or the processing unit 250 (i.e., part of the formation tool, see figure 2) to generate predictions associated with sampling a formation.”); and using a numerical model to determine a formation condition ([0027] “One or more of the parameters measured by the sensors 235 may be used by the simulation engine 240 to determine, predict and/or update a flow regime in the borehole, a drilling fluid filtration rate, a pore pressure model, formation mobility, a pressure distribution history, a drilling fluid circulation history, mudcake parameters and/or drilling fluid ( e.g., filtrate) invasion. Additionally, some or all of these measured parameters may be used by the simulation engine 240 to determine, predict and/or update a mudcake model, a formation model (including a formation fluid model), a mudcake deposition model, a mudcake erosion model, a mudcake compressibility model, a mudcake permeability model, a mudcake desorption model (i.e., examples of numerical model), a sandface pressure and/or a formation porosity.”), wherein inputs for the numerical model include the set of sampling parameters and the set of fluid parameters ([0051] “The inputs utilized by the formation flow simulator 306 may be associated with drilling fluid parameters, parameters related to reservoir data, sampling parameters and/or parameters related to a sampling tool model or tool model.”), wherein the set of fluid parameters includes a contamination level for the sampled fluid determined as a function of time or a function of pumpout volume ([0099] “The predictions generated by the simulation engine 240 may be associated with a history of the pumped fluid contamination as a function of time and/or the volume of fluid pumped from the formation (i.e., history of the contamination level is a parameter for the model).” And [0106] “FIGS. 8 and 9 depict graphs 800 and 900 that represent a filtration rate of drilling fluid into the formation at the sampling location as a function of time.” And [0112] “FIGS. 12 and 13 depict graphs 1200 and 1300 that represent an example relationship between a contamination level of the fluid sample as a function of the volume of the sampled fluid pumped from the formation that may be generated by the formation flow simulator 306.”).
Pop does not teach wherein the numerical model decomposes the function as a sum of a plurality of exponential decays and determines the formation condition based on the decomposition.
Venkataramanan teaches wherein the numerical model decomposes function as a sum of a plurality of exponential decays and determines the formation condition based on the decomposition. ([0045] “These distributions provide information such as the range of pore-sizes in a rock and are empirically related to rock permeability. They are also used to distinguish bound fluid versus free-fluid in a rock. NMR relaxation measurements of bulk hydrocarbons are also used to infer oil viscosity. More recently, two-dimensional measurements, such as diffusion-relaxation, have been used to provide information about fluid typing and saturation (i.e., formation conditions)” where [0126] “The multi-exponential time-decay (for example equation 1) given it of NMR magnetization is characterized by relaxation time constants T 1 , T 2 or diffusion D and corresponding amplitudes ft1(T1), fT2(T2)m fD(D) (i.e., numerical model). Since the relaxation times and/or diffusion constants are expected to be continuous and typically span several decades, these amplitudes are often referred to as relaxation-time or diffusion distributions.” where multi-exponential decay is a plurality of decays, and equation 1 demonstrates an integral, and an integral is just a sum).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the model being a plurality of exponentials as discussed in Venkataramanan to the formation testing tool discussed in Pop for the purpose of being able to differentiate the sample content using techniques like NMR. This is advantageous because NMR is an effective method for pore structure description, permeability, wettability, fluid identification, and quantitative evaluation.
Regarding Claim 2, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches repeating one or more times ([0075] “As described in greater detail below in connection with FIG. 5, the sampling operation(s) performed at block 408 may be iteratively changed, modified or updated dynamically to further refine the sampling operation. In other words, the sampling operation(s) performed at block 408 may be managed or updated in real time to further refine the performance of the sampling operations(s ) (i.e., the steps are repeated one or more times).”): using the numerical model to generate an updated set of sampling parameters ([0093] “At the completion of the initial sampling process (e.g., a preliminary test), the actual measurements made at blocks 508 and 514 may then be processed via the simulation engine 240 to update the planned sampling operation based on the actual measurements (block 516) (i.e., an updated set of sampling parameters would update the planned sampling operation) .”, where [0015] “More specifically, one or more drilling related parameter values and/or one or more sampling-related parameter values may be gathered or measured during drilling or while drilling is temporarily halted. Those gathered or measured parameter values may then be used to update (e.g., modify) the initially selected drilling and/or sampling plan (s).”); using the formation testing tool to obtain additional sampled fluid from the formation according to the updated set of sampling parameters (Fig 5, step 532 sends the user back up to step 508 to repeat through step 510, “perform sampling” (i.e., obtain additional sampled fluid each time 510 is performed again) and down the flow chart. And [0075] “Such real time updating may involve measuring and analyzing formation response or properties and/or formation fluid properties, adjusting one or more drilling parameters ( e.g., drilling fluid flow rate), adjusting a sample fluid flow rate, updating model parameters based on the analysis and then repeating or continuing the sampling operation. One or more sampling operation updates or cycles may be performed until the example process 400 determines that sampling at that particular borehole location or depth is complete.”, where [0073] “Such gathered data may include parameters measured by, for example, LWD or MWD tools (i.e., formation tools). In particular, drilling fluid parameters, borehole temperatures and pressures, borehole geometries, trajectory, etc., formation properties, formation fluid properties (e.g., collected during one or more sampling operations (e.g., during one or more preliminary tests) while the drilling is temporarily stopped), etc. may be measured and gathered for a pre-determined period of time or, alternatively, until a predetermined condition or set of conditions is/are satisfied ( e.g., a particular depth has been reached, one or more measured parameter values are within a certain target range of values, above or below a threshold value, etc.).”); using the formation testing tool to analyze the additional sampled fluid to identify an updated set of fluid parameters for the additional sampled fluid (Fig 5, step 532 sends the user back up to step 508 to repeat through step 510, “perform sampling” (i.e., obtain additional sampled fluid each time 510 is performed again) and down the flow chart. [0075] “Such real time updating may involve measuring and analyzing formation response or properties and/or formation fluid properties, adjusting one or more drilling parameters ( e.g., drilling fluid flow rate), adjusting a sample fluid flow rate, updating model parameters based on the analysis and then repeating or continuing the sampling operation. One or more sampling operation updates or cycles may be performed until the example process 400 determines that sampling at that particular borehole location or depth is complete.”, where [0087] “the identified possible scenarios, plans or processes and the related parameters and parameter values are processed by the simulation engine 240 and/or the processing unit 250 (i.e., part of the formation tool, see figure 2) to generate predictions associated with sampling a formation.”) ; and using the numerical model to generate an updated formation condition ([0027] “One or more of the parameters measured by the sensors 235 may be used by the simulation engine 240 (i.e., numerical model) to determine, predict and/or update a flow regime in the borehole, a drilling fluid filtration rate, a pore pressure model, formation mobility, a pressure distribution history, a drilling fluid circulation history, mudcake parameters and/or drilling fluid ( e.g., filtrate) invasion. Additionally, some or all of these measured parameters may be used by the simulation engine 240 to determine, predict and/or update a mudcake model, a formation model (including a formation fluid model), a mudcake deposition model, a mudcake erosion model, a mudcake compressibility model, a mudcake permeability model, a mudcake desorption model, a sandface pressure and/or a formation porosity.”), wherein inputs for the numerical model further include the updated set of sampling parameters and the updated set of fluid parameters ([0051] “The inputs utilized by the formation flow simulator 306 may be associated with drilling fluid parameters, parameters related to reservoir data, sampling parameters and/or parameters related to a sampling tool model or tool model.”, where [0015] “More specifically, one or more drilling related parameter values and/or one or more sampling-related parameter values may be gathered or measured during drilling or while drilling is temporarily halted. Those gathered or measured parameter values may then be used to update (e.g., modify) the initially selected drilling and/or sampling plan (s).”).
Regarding Claim 3, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches wherein inputs for the one or more of historical fluid parameters for fluid sampled from the formation ([0070] “block 402 may involve retrieving historical data relating to drilling and/or sampling operations (i.e., fluid sample parameters) and using that historical data to evaluate a plurality of possible drilling and/or sampling scenarios, plans or processes. The historical data typically includes parameter values for a plurality of parameters related to drilling and/or sampling operations corresponding to the possible drilling and/or sampling scenarios or plans. Thus, each of the drilling and/or sampling scenarios or plans may include one or more sets of possible drilling and sampling parameters and related historical parameter values, which may have been obtained, for example, during prior drilling and/or sampling activities.”), simulated fluid parameters for fluid sampled from the formation ([0014] “As described in more detail below, each of the plans, scenarios or processes may be analyzed using, for example, a simulation engine, which may include one or more simulators, to enable a relative comparison and/or ranking of the plans, scenarios or processes based on the estimated or predicted sampling results provided by each of the plans, scenarios or processes.”), historical fluid parameters for fluid sampled from a different formation ([0070] “block 402 may involve retrieving historical data relating to drilling and/or sampling operations (i.e., fluid sample parameters) and using that historical data to evaluate a plurality of possible drilling and/or sampling scenarios, plans or processes. The historical data typically includes parameter values for a plurality of parameters related to drilling and/or sampling operations corresponding to the possible drilling and/or sampling scenarios or plans. Thus, each of the drilling and/or sampling scenarios or plans may include one or more sets of possible drilling and sampling parameters and related historical parameter values, which may have been obtained, for example, during prior drilling and/or sampling activities.” Where it can be assumed that drilling of a borehole is not exclusively done in one formation layer, [0018] “of FIG. 1, a borehole 11 is formed in one or more subsurface formations by rotary and/or directional drilling.” Thus the history of a singular borehole can contain more than one formations historical data information), and simulated fluid parameters for fluid sampled from the different formation ([0014] “As described in more detail below, each of the plans, scenarios or processes may be analyzed using, for example, a simulation engine, which may include one or more simulators, to enable a relative comparison and/or ranking of the plans, scenarios or processes based on the estimated or predicted sampling results provided by each of the plans, scenarios or processes.” Where it can be assumed that drilling of a borehole is not exclusively done in one formation layer, [0018] “of FIG. 1, a borehole 11 is formed in one or more subsurface formations by rotary and/or directional drilling.” Thus the history of a singular borehole can contain more than one formations historical data information).
Regarding Claim 4, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches wherein the set of sampling parameters comprises sampling conditions associated with obtaining the sampled fluid ([0051] “The inputs utilized by the formation flow simulator 306 may be associated with drilling fluid parameter, parameters
related to reservoir data, sampling parameters and/or parameters related to a sampling tool model or tool model. (i.e., sampling conditions that are associated with obtaining the sampled fluid)”).
Regarding Claim 5, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches wherein the set of sampling parameters comprises a drawdown rate used for sampling fluid from the formation, a drawdown pressure used for sampling fluid from the formation, an injection rate for injecting fluid from the formation testing tool into the formation during sampling, a buildup pressure measured after sealing the formation testing tool, or a characteristic dimension of the formation testing tool ([0036] “Parameters related to drilling include drillstring geometry, borehole trajectory, drilling fluid circulation rate history, depth of the drillstring, cuttings production and/or rotational speed of the bottomhole assembly. The drillstring geometry may include the dimensions and/or diameter of different components of the bottomhole assembly, which may include the drill bit, the drill collars, the drill pipe and/or the centralizers or stabilizers, etc. The drillstring geometry and/ or location may be utilized to determine drilling fluid flow areas along the borehole trajectory.”, characteristic dimension of the formation testing tool; [0041] “Additionally, the drillstring rotational speed impacts mudcake mechanics and the drilling fluid invasion rate, that is, the rate at which the drilling fluid, primarily filtrate, penetrates the formation F.”, injection rate for injecting fluid from the formation testing into the formation during sampling, and [0059] “Generally, the tool response simulator 308 receives and processes inputs to generate outputs related to a tool operating point, an actual pressure drop (i.e., drawdown pressure) and/or an actual flow rate (i.e., drawdown rate for sampling fluids). The inputs may be associated with a drilling fluid circulation rate, a drilling fluid type and/or a temperature in the borehole.”)
Regarding Claim 7, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches wherein the set of fluid parameters for the sampled fluid comprises analytical results associated with evaluating the sampled fluid ([0075] “Such real time updating may involve measuring and analyzing formation response (i.e., analytical results) or properties and/or formation fluid properties, adjusting one or more drilling parameters ( e.g., drilling fluid flow rate), adjusting a sample fluid flow rate, updating model parameters based on the analysis and then repeating or continuing the sampling operation.”) .
Regarding Claim 8, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches wherein the set of fluid parameters for the sampled fluid further comprises at least one of a mass density for the sampled fluid, a fluid viscosity for the sampled fluid, a fluid resistivity for the sampled fluid, a formation pressure, an estimated formation pressure, an optical density for the sampled fluid, a speed of sound in the sampled fluid, a gas-to-liquid ratio for the sampled fluid, a composition of the sample fluid, or a formation volume factor for the sampled fluid ([0025] “The formation fluid 210 drawn into the LWD tool 200 via the probe 205 may be measured to determine, for example, fluid composition, viscosity, density (i.e., mass density), optical density, absorbance, fluorescence, resistivity and/or conductance, dielectric constant, temperature, etc.”, and [0035] “An estimate of the pressure (i.e., estimated formation pressure) may be determined by the drilling fluid density and a measure of the vertical depth of the drillstring relative to the surface. The pressure may additionally or alternatively be determined from measurements (i.e., formation pressure) obtained by one or more of the sensors 235 (FIG. 2).”, and [0099] “The predictions generated by the simulation engine 240 may be associated with a history of the pumped fluid contamination as a function of time and/or the volume of fluid pumped from the formation.”; a mass density for the sampled fluid, a fluid viscosity for the sampled fluid, a fluid resistivity for the sampled fluid, a formation pressure, an estimated formation pressure, an optical density for the sampled fluid, a composition of the sample fluid, or a formation volume factor for the sampled fluid).
Regarding Claim 10, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches wherein the formation condition comprises one or more of: predicted contamination for additional fluid sampled from the formation as a function of time or pumpout volume; a predicted time at which additional fluid sampled from the formation contains a target amount or less of contamination; a predicted pumpout volume at which additional fluid sampled from the formation contains a target amount or less of contamination; or a predicted lowest level of contamination for additional fluid sampled from the formation ([0112] “FIGS. 12 and 13 depict graphs 1200 and 1300 that represent an example relationship between a contamination level of the fluid sample as a function of the volume of the sampled fluid pumped from the formation that may be generated by the formation flow simulator 306 (i.e., predicted pumpout volume).”, where [0098] “For example, real time control over the sampling operation may be achieved by controlling a sampling pump, estimating an amount of contamination, estimating a volume to be pumped to reach a targeted contamination level and/or controlling a time at which the sample is routed to a sample chamber and/or bottle”, a predicted pumpout volume at which additional fluid sampled from the formation contains a target amount or less of contamination).
Regarding Claim 14, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches wherein the numerical model further generates predicted formation properties including one or more of a formation porosity, a formation permeability, a permeability anisotropy, a formation pressure, a formation relative permeability, a formation capillary pressure, a formation water saturation, a formation residual saturation, a formation phase and total mobility, or a formation height ([0043] “Additionally, the mudcake simulator 304 includes internal variables that are associated with a mudcake mass and/or mudcake compaction. The mudcake mass is associated with a mass of solid material that is deposited on the borehole wall 220. Generally, properties of the mudcake such as, for example, thickness, porosity, permeability, compressibility, strength, filtration rate and/or "stickance," may be monitored”, a formation porosity, a formation permeability).
Regarding Claim 15, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches wherein the numerical model evaluates the formation condition by computing a derivative of one or more fluid parameters of the set of fluid parameters ([0027] “Further, one or more of these measured parameters (i.e., fluid parameters) may be used by the simulation engine 240 to determine, predict and/or update a formation compressibility, a drilling fluid model, a model to estimate formation properties and/or drilling fluid properties, equations of fluid mechanics in the borehole (i.e., equations of fluid mechanics in a borehole are differential equations, aka equations of derivations), a spurt invasion model, a formation flow model and/or a sampling tool performance model.”).
Regarding Claim 17, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches wherein the numerical model applies a noise filter to one or more fluid parameters of the set of fluid parameters ([0028] “The sensors 235 may output analog and/or digital signals, which may be digitized representations of analog signals, processed to reduce noise (i.e., noise filter is applied) and/or to reduce the number of bits used to represent the output (i.e., compressed).”).
Regarding Claim 19, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches wherein the set of fluid parameters includes a contamination level for the sampled fluid ([0099] “The predictions generated by the simulation engine 240 may be associated with a history of the pumped fluid contamination as a function of time and/or the volume of fluid pumped from the formation (i.e., history of the contamination level is a parameter for the model).”).
Regarding Claim 20, Pop and Venkataramanan teaches the limitations of claim 1.
Pop teaches wherein the numerical model evaluates a time or pumpout volume at which a fluid contamination level for fluid from the formation falls or is predicted to fall below a threshold level ([0099] “The predictions generated by the simulation engine 240 may be associated with a history of the pumped fluid contamination as a function of time and/or the volume of fluid pumped from the formation.” Where the history of the pumped fluid contamination from the formation can be determined from [0073] “In particular, drilling fluid parameters, borehole temperatures and pressures, borehole geometries, trajectory, etc. (i.e., where contamination is an etc. option), formation properties, formation fluid properties (e.g., collected during one or more sampling operations (e.g., during one or more preliminary tests) while the drilling is temporarily stopped), etc. may be measured and gathered for a pre-determined period of time or, alternatively, until a predetermined condition or set of conditions is/are satisfied ( e.g., a particular depth has been reached, one or more measured parameter values are within a certain target range of values, above or below a threshold value, etc.).”).
Regarding Claim 21, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches one or more sampling systems for obtaining a sampled fluid from a formation ([0073] “Such gathered data may include parameters measured by, for example, LWD or MWD tools (i.e., formation tools). In particular, drilling fluid parameters, borehole temperatures and pressures, borehole geometries, trajectory, etc., formation properties, formation fluid properties (e.g., collected during one or more sampling operations (e.g., during one or more preliminary tests) while the drilling is temporarily stopped), etc. may be measured and gathered for a pre-determined period of time or, alternatively, until a predetermined condition or set of conditions is/are satisfied ( e.g., a particular depth has been reached, one or more measured parameter values are within a certain target range of values, above or below a threshold value, etc.).”); one or more sensors for analyzing the sampled fluid ([0025] “The LWD tool 200 may also be provided with one or more fluid measurement units 230 and one or more sensors 235, which are collectively configured to measure parameters (e.g., process parameters, formation parameters, etc.). The fluid measurement unit(s) 230 may include, for example, a light absorption spectrometer having a plurality of channels, each of which may correspond to a different wavelength. Thus, the fluid measurement unit( s) 230 may be configured to measure spectral information (i.e., analyze) for fluids drawn from the formation F. This spectral information may be utilized to determine a composition and/or other properties of the fluid. The fluid measurement unit(s) 230 may additionally or alternatively include a mass spectrometer and/or a chromatography unit, an NMR spectrometer, a fluorescence spectrometer, a resistivity measurement unit and/or any other suitable fluid measurement unit.”); one or more processors in communication with the one or more sampling systems and the one or more sensors ([0067] “Although the example methods are described with reference to the flowcharts of FIGS. 4 and 5, persons of ordinary skill in the art will readily appreciate that other methods to implement the bottomhole assembly 100, the fluid measurement unit 230, the sensors 235, the simulation engine 240 and the processing unit 250 of FIG. 2 and the wellbore hydraulics simulator 302, the mudcake simulator 304, the formation flow simulator 306, the tool response simulator 308, the comparator 310, the initiator 312, the sorter 314, theprocessor316 and the identifier 318 of FIG. 3 to optimize planning operations, drilling operations and/or sampling operations may additionally or alternatively be used.” Where flowcharts 4 and 5 demonstrate how the sensors and processors communicate); and a non-transitory computer readable storage medium in communication with the one or more processors, the non-transitory computer readable storage medium containing instructions that, when executed by the one or more processors, cause the one or more processors to perform the method of claim1 (inherent) ([0067]” In particular, a processor or any other suitable device to execute machine readable instructions may retrieve such instructions from a memory device ( e.g., a random access memory (RAM), a read only memory (ROM), etc.) (i.e., nontranistory) and execute those instructions.”).
Regarding Claim 41, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches a computer program product comprising a non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by one or more processors cause the one or more processors to perform the method of claim1 (inherent) ([0067] “Such machine readable instructions (i.e., computer program product) may be executed by one or more of the logging and control computer 160 (FIG. 1), the processing unit 250 (FIG. 2) and/or the processor 316 (FIG. 3). In particular, a processor or any other suitable device to execute machine readable instructions may retrieve such instructions from a memory device ( e.g., a random access memory (RAM), a read only memory (ROM), etc.) and execute those instructions.”).
Regarding Claim 61, Pop and Venkataramanan teaches the limitations of claim 1.
Pop does not teach wherein the decomposing of the level of contamination comprises performing a regularized exponential decomposition in the pumpout volume domain to produce a pump-out volume distribution of exponential components.
Venkataramanan teaches wherein the decomposing of the level of contamination comprises performing a regularized exponential decomposition in the pumpout volume domain to produce a pump-out volume distribution of exponential components ([0108] “FIG. 3 is a plot showing a non-uniform sampling, according to some embodiments. In particular, using eqn. (10), the data shown by curve 310 are sampled uniformly in the
t
domain. Curve 310 is an example of a single exponential in the time-domain into a Gaussian in the
τ
domain with
M
(
t
)
=
e
-
τ
2
/
T
1
.
Using eqn. (11), the sum of measured echoes of the Gaussian directly provides
T
1
0.5
(i.e., decomposing the decay). Thus, if the ω-th moment is desired, then the data need to be sampled non-uniformly in time according to eqn. (10). FIG. 4 plots examples of non-uniform sampling in time domain that can directly provide moments of relaxation or diffusion distribution, according to some embodiments. In particular, plots 410, 412, 414 and 416 represent sampling for co values of 1, 0.75, 0.5, and 0.25 respectively. When 0<ω<1, this leads to finer sampling at the initial part of the data and coarser sampling at the tail end of the data.”) .
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine decomposing the data into a plurality of exponentials as discussed in Venkataramanan to the formation testing tool discussed in Pop for the purpose of being able to differentiate the sample content using techniques like NMR. This is advantageous because NMR is an effective method for pore structure description, permeability, wettability, fluid identification, and quantitative evaluation.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pop and Venkataramanan further in view of Proett et al. (US 20150040657 A1) herein after Proett.
Regarding Claim 6, Pop and Venkataramanan teaches the limitations of claim 5.
Pop does not teach wherein the set of sampling parameters further comprise a pulse sequence, the pulse sequence including one or more modifications to the drawdown rate, the drawdown pressure, the injection rate, or the buildup pressure in an ordered sequence during sampling fluid from the formation.
Proett teaches wherein the set of sampling parameters further comprise a pulse sequence, the pulse sequence including one or more modifications to the drawdown rate, the drawdown pressure, the injection rate, or the buildup pressure in an ordered sequence during sampling fluid from the formation ([0111] “initiating a pulse sequence where each pulse is optimized in response to matching parameters of the diverse reservoir conditions. The optimization may be designed to determine the reservoir properties including stabilized pressure (i.e., build up pressure), actual formation pressure, formation mobility, formation permeability, mudcake properties and formation damage. In one embodiment, the present disclosure provides a basic method involves initiating a pressure pulse that is followed by a series of pulses that are optimized with analytical and or numerical simulation models to minimize operational time and cost in determining reservoir parameters.”, where [0032] “The first drawdown or injection pulse may be determined by the expected formation conditions. For example, controls such as the starting drawdown or injection rate may be applied and the drawdown or injection may continue until a desired pressure, pressure transient, or volume is obtained. In other embodiments, another form of pulse control may be achieved by varying the rate and volume during the pulse to obtain a desired final pressure. A buildup or builddown time may be inserted between the drawdown and injection pulses. A period where there is no flow is induced, referred to as a stabilization time, may also be introduced. The observed pressure transient during this no flow period may be used to determine the next or optimized pulse control parameters (drawdown or injection). In analytical simulations, the pressure response of a sequential drawdown, buildup, injection and builddown test can be expressed in Eq. (1) to Eq. (4)”)
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pop and Venkataramanan further in view of Osborne (US 20150347647 A1)
Regarding Claim 11, Pop and Venkataramanan teaches the limitations of claim 1.
Pop further teaches a predicted lowest level of contamination for additional fluid sampled from the formation, or a predicted duration until additional fluid sampled from the formation contains a target amount or less of contamination ([0113] “Although the cleanup rate is slow, ultimately a low level of contamination may be achieved after a sufficient volume has been pumped. FIG. 13 represents the situation where the sampling operation is performed relatively soon after the sampling depth has been reached. In this case the mudcake is still forming and does not provide an effective barrier to the infiltration of drilling fluid filtrate through the borehole wall. Although the initial cleanup trend is relatively rapid, a limit to the minimum level of sampled fluid contamination is reached at the chosen pumping rate.”, a predicted lowest level of contamination for additional fluid sampled from the formation)
Pop does not teach generating a notification wherein the notification includes one or more of an indication of contamination.
Osborne teaches generating a notification wherein the notification includes one or more of an indication of contamination ([0056] “In one embodiment, the decision support toolkit 137 may be configured to generate haptic vibrations or other tactile notifications to the user's mobile or other computing device. Other types of notifications may include those provided via applications resident on mobile telephony, tablet, or
wearable devices are also possible, such as for example a voice-based output generated to verbally notify farmers or growers of increased risk of contamination or a recommended change in irrigation practice for a specific period of time.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the notification of contamination discussed in Osborne to the contamination levels monitored in Pop for the purpose of having an indicator when the threshold contamination levels are reached. This is advantageous because “generally, hydraulic fracturing involves injection of massive amounts of fluids, such as saltwater, into a well at high pressure to create fractures in rock formations, such as shale, that contain subterranean hydrocarbon reservoirs. Products extracted from a typical oil well involving hydraulic fracturing
are crude oil and natural gas, along with the injected saltwater, which becomes an unwanted byproduct of the process. Over the production lifetime, the percentage of saltwater from a well producing oil or gas increases, and a newly drilled well can initially produce one barrel of saltwater for every two barrels of hydrocarbons extracted,” and the ability to monitor and alert when the level of contaminates in the fluid/oil is low would indicate when there is minimal extra fluids, like saltwater, in the oil being pulled from the ground (e.g., [0004], Oscar).
Claim(s) 62 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pop and Venkataramanan further in view of Lee et al. (US 2020/0072047 A1) hereinafter Lee.
Regarding Claim 62, Pop and Venkataramanan teach the limiations of claim 20.
Pop and Venkataramanan do not teach wherein the evaluation comprises identifying a last dominant peak in a pumpout volume distribution of exponential components.
Lee teaches wherein the evaluation comprises identifying a last dominant peak in a pumpout volume distribution of exponential components (Fig 10 and 11 where the pumpout volume line of best fit is moved to the last (or only) dominant peak of the data, which can be graphed as an exponential, and [0055] “FIG. 12 is a flow-chart diagram of at least a portion of an example implementation of a method (100) of utilizing the RMP filter according to one or more aspects of the present disclosure. The method (100) includes obtaining (110) parameters for a data window that is moved across the data to window locations individually utilized to collectively filter the data. For example, the obtained (110) window parameters may be predetermined settings or user inputs. The obtained (110) parameters include a window size and a window target percentile range between upper and lower percentiles. The window has the same size and target percentile range as the window moves through each location across the data. The window size may be based on number of data points, pumpout volume intervals, or pumpout time intervals. For example, the window size may be a number of data points ranging between five data points and 5,000 data points, a pumpout volume interval ranging between one cubic centimeter (cc) and 100 cc, or a pumpout time interval ranging between five seconds and ten minutes. However, these are merely examples, and other window sizes are also within the scope of the present disclosure. The window target percentile range may be 20%-80%, 40%-60%, or other ranges selected in consideration of noise distribution, computational cost, target and/or expected accuracy, prior knowledge pertaining to the raw measurement data and/or formation, and/or other factors.” where [0048] “During OCM according to one or more aspects of the present disclosure, OD0 is estimated by fitting the asymptotic, exponential model set forth below in Equation (4) to the OD measurement data in the least-squares sense. OD(V)=C−D×V−γ (4) where C is OD0, and where D and γ are the fitting parameters controlling the evolution of contamination.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the use decomposing the top pumpout volume in exponential decays as discussed in Lee to the formation test tool analysis discussed in Pop and Venkataramanan for the purpose of quantifying the pumpout volume coming from a borehole during sampling. This is advantageous because it allows for a more accurate depiction of the fluid being pumped out of the system during sample times, when current methods are found lacking in terms of contamination detection and pressure changes (e.g., [0002], Lee).
Conclusion
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.
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/EMMA ALEXANDER/Patent Examiner, Art Unit 2863
/Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2863
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