Abstract: The present disclosure provides feature data processing methods and devices. One exemplary feature data processing method comprises: classifying features into an important feature set and an auxiliary feature set according to information attribute values of the features; converting features in the auxiliary feature set to hash features; and combining the hash features with features in the important feature set, and setting the combined features as fingerprint features. Training and prediction of to-be-processed data can be performed based on the fingerprint features. With the embodiments of the present disclosure, training dimensions can be more controllable and the amount training data amount can be reduced. Therefore, the efficiency of data processing can be improved.

Abstract: The present disclosure provides question recommendation methods and devices. One exemplary method comprises: acquiring questions and question features corresponding to the questions; processing the question features, the processed question features being in a preset numerical range; and determining a to-be-recommended question according to the questions, a second probability of each question among the questions, and a specified recommendation threshold, wherein the second probability of each question among the questions is obtained by using the processed question features and first probabilities, the first probabilities being obtained based on the question features. By using the methods and devices in the present disclosure, a question to be recommended to a user can be obtained by performing calculation on historical question features, thereby improving accuracy of question recommendation to the user.

Abstract: A method is provided, including: forming an optical computing device having a first plurality of sensing elements selected to measure a characteristic of a sample, generating a transmission function from a first add-on integrated computational element (ICE), and evaluating, with a merit-function and the transmission function of the add-on ICE, a predictive performance of a modified optical computing device that includes the add-on ICE in addition to the first plurality of sensing elements. Also, modifying the first add-on ICE to improve the predictive performance of the modified optical computing device according to the merit-function and a modified transmission function of the add-on ICE.

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: Embodiments of the present invention may share common data among multiple servers. According to one embodiment of the present invention, a code segment is obtained at a first server from a client in response to the client interacting with a first application hosted on the first server, where the code segment is associated with business logic in the first application. Then, the first application is executed based on the code segment.

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 designing an integrated computational element (ICE) includes generating an array of discrete data points and plotting the discrete data points across a predetermined wavelength region. A line shape is then generated that connects to and is constrained by the array of discrete data points, and thereby generates a first transmission function. The discrete data points are then iteratively modified based on one or more performance criteria to generate a second transmission function. A model transmission function corresponding to a model ICE design is then fitted to the second transmission function to identifying a predictive ICE design configured to detect a desired characteristic of interest.

Abstract: Calibration of optical computing devices is achieved using mapping functions that map real detector responses to simulated detector responses which are simulated using high-resolution spectra of traceable optical filters and optical computing device characteristics.

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: The current disclosure describes an automated high-throughput seed sorting system for separating seed via oil and/or moisture content using novel nuclear magnetic resonance (NMR) systems and methods. The disclosed systems and methods for measuring the oil and/or moisture content of a single seed in a low-field time domain NMR instrument are superior in sample throughput and signal-to-noise ratio to conventional NMR systems and methods (free induction decay or spin echo) for single seed oil/moisture measurement.

Abstract: A computer cluster comprising a data storage server and an application server, a computer-implemented method, and a computer readable medium having stored thereon a computer executable program code for processing of resource usage records (e.g. CDRs) is disclosed herein. The computer cluster is operable for supporting operation of database engines providing access to the resource usage records stored in the data storage of the data storage server.

Abstract: An example formation fluid analysis tool includes an optical element and a detector configured to receive light passed through the optical element. The optical element is configured to receive light from a fluid sample and comprises a substrate, an integrated computational element (ICE) fabricated on a first side of the substrate, and an optical filter fabricated on a second side of the substrate opposite the first side.

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 may include collecting measurement data using a first operational sensor and a second operational sensor of a downhole tool, standardizing optical responses of each operational sensor to a master sensor in a tool parameter space to obtain a standardized master sensor response, transforming the standardized master sensor response to a synthetic parameter space response of the master sensor, applying a fluid model with the synthetic parameter space response of the master sensor to predict a fluid characteristic, comparing a first prediction obtained with the fluid model from the first operational sensor with a second prediction obtained with the fluid model from the second operational sensor, determining a fluid characteristic from the first prediction and the second prediction, and optimizing a well testing and sampling operation according to the fluid characteristic.

Abstract: A method of cross-tool optical fluid model validation includes selecting verified field data measured with a first sensor of an existing tool as validation fluids and selecting a second sensor for a new tool or on a different existing tool. The method may also include applying cross-tool optical data transformation to the validation fluids in a tool parameter space from the first sensor to the second sensor, and calculating the synthetic optical responses of the second sensor on the validation fluids through cross-space data transformation. The method may further include determining a new or adjusting an existing operational fluid model of the second sensor in a synthetic parameter space according to the candidate model performance evaluated on the validation fluids, and optimizing well testing and sampling operation based on real-time estimated formation fluid characteristics using the validated fluid models of the second sensor in an operating tool.

Abstract: Embodiments of the present invention may share common data among multiple servers. According to one embodiment of the present invention, a code segment is obtained at a first server from a client in response to the client interacting with a first application hosted on the first server, where the code segment is associated with business logic in the first application. Then, the first application is executed based on the code segment.

Abstract: Embodiments of the present invention may share common data among multiple servers. According to one embodiment of the present invention, a code segment is obtained at a first server from a client in response to the client interacting with a first application hosted on the first server, where the code segment is associated with business logic in the first application. Then, the first application is executed based on the code segment.

Abstract: The current disclosure describes an automated high-throughput small object sorting system for separating small object via oil and/or moisture content using novel nuclear magnetic resonance (NMR) systems and methods. The disclosed systems and methods for measuring the oil and/or moisture content of a single small object in a low-field time domain NMR instrument are superior in sample throughput and signal-to-noise ratio to conventional NMR systems and methods (free induction decay or spin echo) for single small object oil/moisture measurement.