Abstract: A system can include a processor; memory operatively coupled to the processor; and processor-executable instructions stored in the memory to instruct the system to: receive a marker on a well log for a well in a geographic region; and iteratively propagate the marker automatically to a plurality of well logs for other wells in the geographic region.

Abstract: A system can include a processor; memory operatively coupled to the processor; and processor-executable instructions stored in the memory to instruct the system to: receive a marker on a well log for a well in a geographic region; and iteratively propagate the marker automatically to a plurality of well logs for other wells in the geographic region.

Abstract: A subsurface structure identification system includes one or more processors and a memory coupled to the one or more processors. The memory is encoded with instructions that when executed by the one or more processors cause the one or more processors to provide a convolutional neural network trained to identify a subsurface structure in an input migrated seismic volume, and to partition the input migrated seismic volume into multi-dimensional sub-volumes of seismic data. The instructions also cause the one or more processors to process each of the multi-dimensional sub-volumes of seismic data in the convolutional neural network, and identify the subsurface structure in the input migrated seismic volume based on a probability map of the input migrated seismic volume generated by the convolutional neural network.

Abstract: A system can include a processor; memory operatively coupled to the processor; and processor-executable instructions stored in the memory to instruct the system to: receive a marker on a well log for a well in a geographic region; and iteratively propagate the marker automatically to a plurality of well logs for other wells in the geographic region.

Abstract: Methods, computing systems, and computer-readable media for multi-scale modeling. The method includes determining a first matrix for a plurality of fine cells of a model based at least in part on a physical property value represented by respective fine cells, identifying one or more overlapped cells of the plurality of fine cells that are part of at least two of the plurality of subdomains, and determining a second matrix. Determining the second matrix includes determining an intermediate product by multiplying the first matrix by a prolongation matrix, which includes predicting a row of zeros in the intermediate product for the plurality of fine cells that are not the one or more overlapped cells and are not part of the at least two of the plurality of subdomains that include the one or more overlapped cells. Determining the second matrix also includes multiplying the intermediate product by a restriction matrix.

Abstract: Methods, apparatuses, and computer-readable media are set forth for logging oil and gas events using a combination of a primary database that stores event data for an oil and gas event along with a blockchain ledger that stores one or more identifying characteristics of the event (e.g., a hash of the event data), thereby enabling the event data to be verified. By utilizing the combination of a primary database and a blockchain ledger, the blockchain ledger is not required to store all of the data associated with an event. As such, where an oil and gas event is associated with a large volume of data, the size and thus the processing overhead associated with the blockchain ledger may be reduced.

Abstract: Systems and methods for simulating fluid properties in a production system include receiving data from a sensor. The data represents a first property of a fluid that is measured by the sensor. A second property of the fluid is estimated based at least in part on the measured first property. A third property of the fluid is calculated using the estimated second property. Calculating the third property includes running a first simulation on a first simulator and running a second simulation on a second simulator. The first and second simulations at least partially overlap in the time domain. It is then determined whether results of the first and second simulations converge to a common value.

Abstract: Methods, computing systems, and computer-readable media for multi-scale modeling. The method includes determining a first matrix for a plurality of fine cells of a model based at least in part on a physical property value represented by respective fine cells, identifying one or more overlapped cells of the plurality of fine cells that are part of at least two of the plurality of subdomains, and determining a second matrix. Determining the second matrix includes determining an intermediate product by multiplying the first matrix by a prolongation matrix, which includes predicting a row of zeros in the intermediate product for the plurality of fine cells that are not the one or more overlapped cells and are not part of the at least two of the plurality of subdomains that include the one or more overlapped cells. Determining the second matrix also includes multiplying the intermediate product by a restriction matrix.