Abstract: A method for shale fracturing includes determining dynamic-elastic properties of a shale deposit in a geological formation. A training database is generated by three-dimensional fracture modeling. A neural network is generated in response to output results of the training database. The shale fracturing may then be performed based on the neural network.

Abstract: Dimensionality reduction systems and methods facilitate visualization, understanding, and interpretation of high-dimensionality data sets, so long as the essential information of the data set is preserved during the dimensionality reduction process. In some of the disclosed embodiments, dimensionality reduction is accomplished using clustering, evolutionary computation of low-dimensionality coordinates for cluster kernels, particle swarm optimization of kernel positions, and training of neural networks based on the kernel mapping. The fitness function chosen for the evolutionary computation and particle swarm optimization is designed to preserve kernel distances and any other information deemed useful to the current application of the disclosed techniques, such as linear correlation with a variable that is to be predicted from future measurements. Various error measures are suitable and can be used.

Abstract: A method includes obtaining a measurement of one or more properties of a downhole fluid using a fluid analysis tool. The fluid analysis tool includes fluid sensors and one or more processors coupled with the fluid sensors. A first prediction is generated using the measurement from the fluid sensors. A second prediction is generated using an adaptive neuro-fuzzy inference system based on the first prediction of the properties.

Abstract: System and methods for downhole fluid analysis are provided. Measurements are obtained from one or more downhole sensors along a current section of wellbore within a subsurface formation. The measurements obtained from the one or more downhole sensors are transformed into principal spectroscopy component (PSC) data. At least one fluid composition or property is estimated for the current section of the wellbore, based on the PSC data and a fluid analysis model. The fluid analysis model is refined for one or more subsequent sections of the wellbore within the subsurface formation, based at least partly on the fluid composition or property estimated for the current section of the wellbore.

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 system includes an optical computing device having an optical multiplexer that receives a sample light generated by an optical interaction between a sample and an illumination light is provided. The system includes sensing elements that optically interact with the sample light to generate modified lights, and a detector that measures a property of the modified lights separately. Linear and nonlinear models for processing data collected with the above system to form high-resolution spectra are also provided. Methods for designing optimal optical multiplexers for optimal reconstruction of high-resolution spectra are also provided.

Abstract: System and methods for downhole fluid classification are provided. Measurements are obtained from one or more downhole sensors located along a current section of wellbore within a subsurface formation. The measurements obtained from the one or more downhole sensors are transformed into principal spectroscopy component (PSC) data. One or more fluid types are identified for the current section of the wellbore within the subsurface formation, based on the PSC data and a fluid classification model. The fluid classification model is refined for one or more subsequent sections of the wellbore within the subsurface formation, based at least partly on the one or more fluid types identified for the current section of the wellbore.

Abstract: Apparatus, methods, and systems related to a thin-layer spectroelectrochemistry cell; electrically coupling a second end of a working electrical wire lead, a second end of a counter electrical wire lead, and a second end of a reference electrical wire lead to a potentiostat; introducing a conductive fluid into a cell body in the spectroelectrochemistry cell; introducing a detection species into the cell body; introducing a sample into the cell body; applying a voltage potential across the transparent sample window to drive an electrochemical reaction between the detection species and the sample in the transparent sample window fluid; transmitting electromagnetic radiation into an optical path through the transparent sample window, thereby optically interacting the electromagnetic radiation with the transparent sample window fluid to generate modified electromagnetic radiation; receiving the modified electromagnetic radiation with a detector; and generating an output signal corresponding to a characteristic of

Abstract: A method for ruggedizing an ICE design, fabrication and application with neural networks as disclosed herein includes selecting a database for integrated computational element (ICE) optimization is provided. The method includes adjusting a plurality of ICE operational parameters according to an environmental factor recorded in the database and simulating environmentally compensated calibration inputs. The method includes modifying a plurality of ICE structure parameters to obtain an ICE candidate structure having improved performance according to a first algorithm applied to the database and validating the ICE candidate structure with an alternative algorithm applied to the database. Further, the method includes determining a plurality of manufacturing ICEs based on the validation with the first algorithm and the alternative algorithm, and fabricating one of the plurality of manufacturing ICEs.

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: Near real-time methodologies for maximizing return-on-fracturing-investment for shale fracturing. An example system can calculate, based on sonic data and density data, mechanical properties and closure stress of a portion of shale rocks for fracture modeling. The system can generate one or more rock mechanical models based on the mechanical properties and closure stress of the portion of shale rocks, and perform one or more fracture modeling simulations based on one or more treatment parameter values. Based on the one or more fracture modeling simulations, the system can generate a neural network model which predicts a fracture productivity indicator of an effective propped area (EPA) and/or an effective propped length (EPL), and calculate a return-on-fracturing-investment (ROFI) based on the EPA or EPL predicted by the neural network model.

Abstract: Systems and methods for simulating optical sensor response data for fluids in a wellbore are disclosed herein. A system comprises a downhole tool, an optical sensor coupled to the downhole tool, and a sensor information mapping module. The sensor information mapping module is operable to receive sensor response information associated with the optical sensor and a first fluid, receive sensor spectra information associated with the optical sensor, and receive fluid spectroscopy information associated with the first fluid. The sensor information mapping module is also operable to determine a transformation matrix using the sensor response information, the sensor spectra information, and the fluid spectroscopy information, and determine, using the transformation matrix, simulated sensor response information associated with the optical sensor and a second fluid.

Abstract: A method for shale fracturing includes determining dynamic-elastic properties of a shale deposit in a geological formation. A training database is generated by three-dimensional fracture modeling. A neural network is generated in response to output results of the training database. The shale fracturing may then be performed based on the neural network.

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 an excitation element into rotational oscillations. A detector produces a response signal correlating to the detected oscillating movement of the excitation element. Circuitry onboard the apparatus utilizes the drive and response signals to determine the fluid viscosity.

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: Various embodiments include apparatus and methods to utilize fluid phase behavior interpretation to increase sensor measurement accuracy. In some embodiments, a downhole sensor measures detector responses within a measurement sample of a downhole fluid. The measured detector responses are acquired from the downhole sensor. A correlation factor is generated as a scalar product between a vector of the measured detector responses and a vector of known responses. The correlation factor has a value within a fixed interval, one end of the fixed interval corresponding to a high correlation status and an opposite end of the fixed interval corresponding to an uncorrelated status. The correlation factor is compared to a correlation threshold for a specified material and sets of data having correlation factors greater than the correlation threshold are identified.

Abstract: A method includes obtaining a plurality of master sensor responses with a master sensor in a set of training fluids and obtaining node sensor responses in the set of training fluids. A linear correlation between a compensated master data set and a node data set is then found for a set of training fluids and generating node sensor responses in a tool parameter space from the compensated master data set on a set of application fluids. A reverse transformation is obtained based on the node sensor responses in a complete set of calibration fluids. The reverse transformation converts each node sensor response from a tool parameter space to the synthetic parameter space, and uses transformed data as inputs of various fluid predictive models to obtain fluid characteristics. The method includes modifying operation parameters of a drilling or a well testing and sampling system according to the fluid characteristics.

Abstract: A method including selecting candidate sensors for pooled calibration and determining a multivariate fluid characterization model with the pooled sensors is provided. The method includes determining a virtual master kernel standardization model with the pooled sensors, implementing a calibration result into a processor circuit and determining a value of a fluid characteristic by applying the multivariate fluid composition model to a plurality of responses obtained from a plurality of sensor responses to the fluid sample. The plurality of responses may be obtained from the plurality of sensor responses using the virtual master kernel standardization model. The method includes optimizing a wellbore operation based on the value of the fluid characteristic. A device for implementing the above method is also provided.

Abstract: Two or more Integrated Computational Element (“ICE”) structures are designed and utilized in an optical computing device to combinatorily reconstruct spectral patterns of a sample. To design the ICE structures, principal component analysis (“PCA”) loading vectors are derived from training spectra. Thereafter, two or more ICE structures having spectral patterns that match the PCA loading vectors are selected. The selected ICE structures may then be fabricated and integrated into an optical computing device. During operation, the ICE structures are used to reconstruct high resolution spectral data of the samples which is utilized to determine a variety of sample characteristics.

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.