Abstract: A method comprises determining an adaptive fluid predictive model calibrated with a plurality of types of sensor data, wherein the plurality of types of sensor responses comprise a first type of sensor response associated with a synthetic parameter space and a second type of sensor response associated with a tool parameter space. The method comprises applying the adaptive fluid predictive model to one or more fluid samples from field measurements obtained from a tool deployed in a wellbore formed in a subterranean formation and determining a value of a fluid answer product prediction with the applied adaptive fluid predictive model. The method comprises facilitating a wellbore operation with the tool based on the value of the fluid answer product prediction.

Abstract: A method comprises determining an adaptive fluid predictive model calibrated with a plurality of types of sensor data, wherein the plurality of types of sensor responses comprise a first type of sensor response associated with a synthetic parameter space and a second type of sensor response associated with a tool parameter space. The method comprises applying the adaptive fluid predictive model to one or more fluid samples from field measurements obtained from a tool deployed in a wellbore formed in a subterranean formation and determining a value of a fluid answer product prediction with the applied adaptive fluid predictive model. The method comprises facilitating a wellbore operation with the tool based on the value of the fluid answer product prediction.

Abstract: The subject disclosure provides for a method of optical sensor calibration implemented with neural networks through machine learning to make real-time optical fluid answer product prediction adapt to optical signal variation of synthetic and actual sensor inputs integrated from multiple sources. Downhole real-time fluid analysis can be performed by monitoring the quality of the prediction with each type of input and determining which type of input generalizes better. The processor can bypass the less robust routine and deploy the more robust routine for remainder of the data prediction. Operational sensor data can be incorporated from a particular optical tool over multiple field jobs into an updated calibration when target fluid sample compositions and properties become available.

Abstract: The disclosed embodiments include systems and methods to perform in-situ analysis of reservoir fluids. In some embodiments, the system includes a first vial containing a first insulating cylinder having a first internal cavity for storing electrolytes, a capillary tube, and a first sealable end having a first seal that prevents the electrolytes that are stored in the first internal cavity from flowing through the first sealable end while the first seal remains intact. The system also includes a second vial containing a second insulating cylinder having a second internal cavity for receiving the electrolytes that are stored in the first insulating cylinder, and a second sealable end having a second seal. The system further includes a tube positioned between the first vial and the second vial, where the tube provides at least one fluid flow path between the first vial and the second vial.

Abstract: The disclosed embodiments include systems and methods to perform in-situ analysis of reservoir fluids. In some embodiments, the system includes a first vial containing a first insulating cylinder having a first internal cavity for storing electrolytes, a capillary tube, and a first sealable end having a first seal that prevents the electrolytes that are stored in the first internal cavity from flowing through the first sealable end while the first seal remains intact. The system also includes a second vial containing a second insulating cylinder having a second internal cavity for receiving the electrolytes that are stored in the first insulating cylinder, and a second sealable end having a second seal. The system further includes a tube positioned between the first vial and the second vial, where the tube provides at least one fluid flow path between the first vial and the second vial.

Abstract: The subject disclosure provides for a method of optical sensor calibration implemented with neural networks through machine learning to make real-time optical fluid answer product prediction adapt to optical signal variation of synthetic and actual sensor inputs integrated from multiple sources. Downhole real-time fluid analysis can be performed by monitoring the quality of the prediction with each type of input and determining which type of input generalizes better. The processor can bypass the less robust routine and deploy the more robust routine for remainder of the data prediction. Operational sensor data can be incorporated from a particular optical tool over multiple field jobs into an updated calibration when target fluid sample compositions and properties become available.

Abstract: Automated assessment of registration quality, focus, and area defects in sequentially acquired images, such as images acquired by a digital microscope, is disclosed. In one embodiment, acquired images are registered and whole-image defects are automatically detected based on a figure of merit generated by the registration process. In related implementations, area defects may be automatically detected by calculating correlations in localized image regions for images acquired in different imaging rounds.

Abstract: Methods for measuring liver fat mass are provided. One method includes acquiring dual-energy two-dimensional (2D) scan information from a dual-energy X-ray scan of a body and generating a dual-energy X-ray image of the body using the 2D scan information. The method further includes identifying a region of interest using the dual-energy X-ray image and determining a subcutaneous fat mass for each of a plurality of sections of the region of interest. The method also includes determining a liver fat mass for the region of interest based on the determined subcutaneous fat mass for each of the plurality of sections.

Abstract: Methods for measuring liver fat mass are provided. One method includes acquiring dual-energy two-dimensional (2D) scan information from a dual-energy X-ray scan of a body and generating a dual-energy X-ray image of the body using the 2D scan information. The method further includes identifying a region of interest using the dual-energy X-ray image and determining a subcutaneous fat mass for each of a plurality of sections of the region of interest. The method also includes determining a liver fat mass for the region of interest based on the determined subcutaneous fat mass for each of the plurality of sections.

Abstract: Automated assessment of registration quality, focus, and area defects in sequentially acquired images, such as images acquired by a digital microscope, is disclosed. In one embodiment, acquired images are registered and whole-image defects are automatically detected based on a figure of merit generated by the registration process. In related implementations, area defects may be automatically detected by calculating correlations in localized image regions for images acquired in different imaging rounds.

Abstract: The invention relates generally to a process of analyzing and visualizing the expression of biomarkers in an individual cell wherein the cell is examined to develop patterns of expression by using a grouping algorithm, and a system to perform and display the analysis.

Abstract: The invention relates generally to a process of analyzing and visualizing the expression of biomarkers in individual cells wherein the cells are examined to develop patterns of expression by using a grouping algorithm, and a system to perform and display the analysis.

Abstract: The invention relates generally to a process of analyzing and visualizing the expression of biomarkers in individual cells wherein the cells are examined to develop patterns of expression by using a grouping algorithm, and a system to perform and display the analysis

Abstract: The present application discloses a technique for obtaining and storing data on expression of multiple biomarkers in individual cells or the compartments of individual cells in a tissue specimen and methods of utilizing that data to create groups, the members of which share some degree of similarity greater than the general population from which the data is drawn, by an analysis of digital images of a portion of the tissue specimen which has been iteratively stained to generate optical signals, typically fluorescent, reflective of the amount of each of the biomarkers examined.