Abstract: Techniques for modeling a wellbore fluid that includes a base fluid and one or more fluid additives includes identifying a target viscosity profile of the wellbore fluid; determining an initial set of values of the fluid additives that are based at least in part on the target viscosity profile; determining, with one or more non-linear predictive models, a computed viscosity profile of the wellbore fluid and a computed set of values of the fluid additives based, at least in part, on the initial set of values of the fluid additives; comparing the computed viscosity profile and at least one of the computed set of values with a specified criteria of the wellbore fluid; and preparing, based on the comparison, an output including the computed viscosity profile and at least one of the computed set of values of a resultant wellbore fluid.

Abstract: Systems and methods for optical fluid identification approximation and calibration are described herein. One example method includes populating a database with a calculated pseudo optical sensor (CPOS) response of a first optical tool to a first sample fluid. The CPOS response of the first optical tool may be based on a transmittance spectrum of a sample fluid and may comprise a complex calculation using selected components of the first optical tool. A first model may be generated based, at least in part, on the database. The first model may receive as an input an optical sensor response and output a predicted fluid property. A second model may also be generated based, at least in part, on the database. The second model may receive as an input at least one known/measured fluid/environmental property value and may output a predicted pseudo optical sensor response of the first optical tool.

Abstract: Various embodiments include apparatus and methods to perform a correlation of data and/or a statistical analysis of data. A correlation of data can include generating a scalar product of measured responses with known responses and using a threshold to determine a correlation of the data. Statistical analysis of data can include generating a statistical measure of measurement data, comparing the statistical measure to a threshold value, and determining phase status of a fluid. Additional apparatus, systems, and methods are disclosed.

Abstract: The disclosed embodiments include a method, apparatus, and computer program product for generating a cross-sensor standardization model. For example, one disclosed embodiment includes a system that includes at least one processor; at least one memory coupled to the at least one processor and storing instructions that when executed by the at least one processor performs operations comprising selecting a representative sensor from a group of sensors comprising at least one of same primary optical elements and similar synthetic optical responses and calibrating a cross-sensor standardization model based on a matched data pair for each sensor in the group of sensors and for the representative sensor. In one embodiment, the at least one memory coupled to the at least one processor and storing instructions that when executed by the at least one processor performs operations further comprises generating the matched data pair, wherein the matched data pair comprises calibration input data and calibration output data.

Abstract: A photometric system design methodology employs genetic algorithms to optimize the selection of optical elements for inclusion in the photometric system in order to improve system performance with respect to environmental conditions (i.e., to “ruggedize” the photometric system). The genetic algorithms utilize a multi-objective fitness function to evolve simulated optical element selection, which may be a combination of optical filters and integrated computational elements.

Abstract: Disclosed are systems and methods for calibrating integrated computational elements. One method includes measuring with a spectrometer sample interacted light comprising spectral data derived from one or more calibration fluids at one or more calibration conditions, the one or more calibration fluids circulating in a measurement system, programming a virtual light source based on the spectral data, simulating the spectral data with the virtual light source and thereby generating simulated fluid spectra corresponding to the spectral data, conveying the simulated fluid spectra to the one or more ICE and thereby generating corresponding beams of optically interacted light, and calibrating the one or more ICE based on the corresponding beams of optically interacted light.

Abstract: This disclosure includes methods for designing a simplified Integrated Computational Element (ICE) and for optimizing a selection of a combination of ICE designs. A method for fabricating a simplified ICE having one or more film layers includes predicting an optimal thickness of each of the one or more film layers of the simplified ICE using a neural network. A method for re-calibrating the fabricated ICE elements for system implementation is also disclosed. The disclosure also includes the simplified ICE designed by and the ICE combination selected by the disclosed methods. The disclosure also includes an information handling system with machine-readable instructions to perform the methods disclosed herein.

Abstract: An apparatus for determining the density of a fluid in a flowstream is disclosed. The apparatus comprises a vibrating tube (12) having a bore and a vibrating region. The apparatus also comprises a housing (16) to support the vibrating region. The apparatus further comprises a vibration source (22) and a vibration detector (24) coupled to the vibrating tube (12), and one or more sensors (26) coupled to the housing (16), said one or more sensors substantially oriented toward the vibrating region of the vibrating tube.

Abstract: A system for integrated computational element (“ICE”) design optimization and analysis utilizes a genetic algorithm to evolve layer thickness of each fixed ICE structure using a constrained multi-objective merit function. The system outputs a ranked representative group of ICE design candidates that may be used for further fabricability study, ICE combination selection, efficient statistical analysis and/or feature characterization.

Abstract: Disclosed are systems and methods that use discriminant analysis techniques and processing in order to reduce the time required to determine chemical and/or physical properties of a substance. One method includes optically interacting a plurality of optical elements with one or more known substances, each optical element being configured to detect a particular characteristic of the one or more known substances, generating an optical response from each optical element corresponding to each known substance, wherein each known substance corresponds to a known spectrum stored in an optical database, and training a neural network to provide a discriminant analysis classification model for an unknown substance, the neural network using each optical response as inputs and one or more fluid types as outputs, and the outputs corresponding to the one or more known substances.

Abstract: An apparatus to determine fluid viscosities downhole in real-time includes a housing and an excitation element positioned therein. Electrical circuitry provides a drive signal that excites movement of the excitation element. A detector produces a response signal correlating to the detected rotational or oscillating movement of the excitation element. Circuitry onboard the apparatus utilizes the drive and response signals to determine the fluid viscosity.

Abstract: A system for pressure testing a formation includes a downhole tool configured to measure formation pressure, storage containing pressure parameters of a plurality of simulated formation pressure tests, and a formation pressure test controller coupled to the downhole tool and the storage. For each of a plurality of sequential pressure testing stages of a formation pressure test, the formation pressure test controller 1) retrieves formation pressure measurements from the downhole tool; 2) identifies one of the plurality of simulated formation pressure tests comprising pressure parameters closest to corresponding formation pressure values derived from the formation pressure measurements; and 3) determines a flow rate to apply by the downhole tool in a next stage of the test based on the identified one of the plurality of simulated formation pressure tests.

Abstract: Improved systematic inversion methodology applied to formation testing data interpretation with spherical, radial and/or cylindrical flow models is disclosed. A method of determining a parameter of a formation of interest at a desired location comprises directing a formation tester to the desired location in the formation of interest and obtaining data from the desired location in the formation of interest. The obtained data relates to a first parameter at the desired location of the formation of interest. The obtained data is regressed to determine a second parameter at the desired location of the formation of interest. Regressing the obtained data comprises using a method selected from a group consisting of a deterministic approach, a probabilistic approach, and an evolutionary approach.

Abstract: In some embodiments, an apparatus and a system, as well as a method and an article, may operate to receive a vibration signal having a frequency and a characteristic (e.g., voltage) proportional to the vibration amplitude of a tube in a vibrating tube density sensor. Further activity may include transmitting the density of a fluid flowing through the tube based on the frequency and an elastic modulus of the tube determined by the value of the characteristic. Additional apparatus, systems, and methods are described.

Abstract: A method of determining a reservoir parameter of a subterranean formation comprising: initiating an initial pressure pulse in the subterranean formation; initiating a series of subsequent pressure pulses in the subterranean formation until the reservoir parameter may be determined, wherein each subsequent pressure pulse is optimized utilizing analytical and/or numerical simulation models; and determining the reservoir parameter.

Abstract: Predicting gas saturation of a formation using neural networks. At least some of the illustrative embodiments include obtaining a gamma count rate decay curve one each for a plurality of gamma detectors of a nuclear logging tool (the gamma count rate decay curves recorded at a particular borehole depth), applying at least a portion of each gamma count rate decay curve to input nodes of a neural network, predicting a value indicative of gas saturation of a formation (the predicting by the neural network in the absence of a formation porosity value supplied to the neural network), and producing a plot of the value indicative of gas saturation of the formation as a function of borehole depth.

Abstract: A method of calibration transfer for a testing instrument includes: collecting a first sample; generating a standard response of a first instrument based, at least in part, on the first sample; and performing instrument standardization of a second instrument based, at least in part, on the standard response of the first instrument. Data corresponding to a second sample is then obtained using the second instrument and a component of the second sample is identified based, at least in part, on a calibration model.

Abstract: Techniques for modeling a wellbore fluid that includes a base fluid and one or more fluid additives includes identifying a target viscosity profile of the wellbore fluid; determining an initial set of values of the fluid additives that are based at least in part on the target viscosity profile; determining, with one or more non-linear predictive models, a computed viscosity profile of the wellbore fluid and a computed set of values of the fluid additives based, at least in part, on the initial set of values of the fluid additives; comparing the computed viscosity profile and at least one of the computed set of values with a specified criteria of the wellbore fluid; and preparing, based on the comparison, an output including the computed viscosity profile and at least one of the computed set of values of a resultant wellbore fluid.

Abstract: Various embodiments include apparatus and methods to provide pipe analysis, annulus analysis, or one or more combinations of pipe analysis and annulus analysis with respect to one or more pipes in a wellbore. The analysis can include application of clustering and classification methods with respect to the status and the environment of the one or more pipes in the wellbore. In various embodiments, the clustering and classification can be used in characterizing borehole annular material including cement bond quality evaluation. Additional apparatus, systems, and methods are disclosed.

Abstract: Processing gamma count rate decay curves using neural networks. At least some of the illustrative embodiments are methods comprising obtaining a gamma count rate decay curve one each for a plurality of gamma detectors of a nuclear logging tool (the gamma count rate decay curves recorded at a particular borehole depth), applying the gamma count rate decay curves to input nodes of a neural network, predicting by the neural network a geophysical parameter of the formation surrounding the borehole, repeating the obtaining, applying and predicting for a plurality of borehole depths, and producing a plot of the geophysical parameter of the formation as a function of borehole depth.