Abstract: Embodiments are directed to managing and improving a drilling and completions process at a hydrocarbon extraction site, and to optimizing resource allocation at a hydrocarbon extraction site/region. In one scenario, a computer system accesses data generated by hardware sensors implemented by drilling and completion equipment at a hydrocarbon extraction site. The computer system formats the sensor data into a form readable by a data mining algorithm, and mines the formatted sensor data to identify characteristics related to the drilling and completion process. The computer system also accesses and integrates historical data related to the drilling and completion equipment at the hydrocarbon extraction site. The computer system then computes drilling and completion performance indicators that identify inefficiencies based on the characteristics identified for the equipment and based on the accessed historical data. Then, a remediation step is performed to resolve the identified inefficiency.

Abstract: Embodiments are directed to automatically detecting an event in a production curve, generating a production estimate using a quantile regression and to performing a probabilistic decline curve analysis. In one scenario, a computer system identifies a candidate break point in a production decline curve which represents a decline in material production at a well. The computer system identifies one trend for the production decline curve occurring before the candidate break point and identifies a second trend for the production decline curve occurring after the candidate break point. The computer system calculates the difference between the first material production decline estimate and the second material production decline estimate and identifies the candidate break points where the difference between the first material production decline estimate and the second material production decline estimate is beyond a threshold value.

Abstract: Embodiments are directed to identifying and implementing hydrocarbon production opportunities including recompletion opportunities, new vertical drill target opportunities, and horizontal or deviated well target opportunities. Computer systems access multi-disciplinary data, perform data validation and pre-processing on the data, identify field development opportunities by identifying candidates, forecasting production at those candidates, generating an uncertainty quantification, and vetting and validating the data. The computer systems then list the viable well target opportunities including recompletion opportunities, vertical new drill target opportunities and deviated and horizontal target opportunities.

Abstract: In accordance with various embodiments of the disclosed subject matter, a smart surveillance and diagnostics system for oil and gas field surface environment via unmanned aerial vehicle (UAV) and cloud computing are provided. Methods and systems provide various functionality including performing, by multiple GPUs or HPCs, a fast pair-wise registration process, a mask setting process, a background generation process, a foreground generation process using a parallel computation infrastructure, a deep learning classification process, and performing anomalism detection (including vision, acoustic and gas concentration) and 3D augmented reality and 2D Panorama view reconstruction under a variety of conditions.

Abstract: Embodiments are directed to managing and improving a drilling and completions process at a hydrocarbon extraction site, and to optimizing resource allocation at a hydrocarbon extraction site/region. In one scenario, a computer system accesses data generated by hardware sensors implemented by drilling and completion equipment at a hydrocarbon extraction site. The computer system formats the sensor data into a form readable by a data mining algorithm, and mines the formatted sensor data to identify characteristics related to the drilling and completion process. The computer system also accesses and integrates historical data related to the drilling and completion equipment at the hydrocarbon extraction site. The computer system then computes drilling and completion performance indicators that identify inefficiencies based on the characteristics identified for the equipment and based on the accessed historical data. Then, a remediation step is performed to resolve the identified inefficiency.

Abstract: Embodiments are directed to performing material balance analysis for tanks in a petroleum reservoir and to performing dual porosity material balance analysis. In one scenario, a computer system divides a reservoir into multiple tank blocks, where at least two tank blocks are adjacent. The adjacent tanks are connected at a tank block boundary so that materials are permitted to travel between the tank blocks. The computer system determines flow rate between adjacent tank blocks proportional to the difference in tank block pressures. Then, upon making this determination, the computer system determines material balance for at least some of the tank blocks in the reservoir through influx and efflux of material across the tank block boundary. The material balance includes a determined material balance for one of the adjacent tank blocks and a determined material balance for the other adjacent tank block.

Abstract: Embodiments are directed to performing material balance analysis for tanks in a petroleum reservoir and to performing dual porosity material balance analysis. In one scenario, a computer system divides a reservoir into multiple tank blocks, where at least two tank blocks are adjacent. The adjacent tanks are connected at a tank block boundary so that materials are permitted to travel between the tank blocks. The computer system determines flow rate between adjacent tank blocks proportional to the difference in tank block pressures. Then, upon making this determination, the computer system determines material balance for at least some of the tank blocks in the reservoir through influx and efflux of material across the tank block boundary. The material balance includes a determined material balance for one of the adjacent tank blocks and a determined material balance for the other adjacent tank block.