Real-Time Minimization of Mechanical Specific Energy with Multivariable Extremum Seeking

Drilling more efficiently and with less non-productive time (NPT) is one of the key enablers to reduce field development costs. In this work, we investigate the application of a data-driven optimization method called extremum seeking (ES) to achieve more efficient and safe drilling through automatic real-time minimization of the mechanical specific energy (MSE). The ES algorithm gathers information about the current downhole conditions by performing small tests with the applied weight on bit (WOB) and drill string rotational rate (RPM) while drilling and automatically implements optimization actions based on the test results. The ES method does not require an a priori model of the drilling process and can thus be applied even in instances when sufficiently accurate drilling models are not available. The proposed algorithm can handle various drilling constraints related to drilling dysfunctions and hardware limitations. The algorithm’s performance is demonstrated by simulations, where the algorithm successfully finds and maintains the optimal WOB and RPM while adhering to drilling constraints in various settings. The simulations show that the ES method is able to track changes in the optimal WOB and RPM corresponding to changes in the drilled formation. As demonstrated in the simulation scenarios, the overall improvements in rate of penetration (ROP) can be up to 20–170%, depending on the initial guess of the optimal WOB and RPM obtained from e.g., a drill-off test or a potentially inaccurate model. The presented algorithm is supplied with specific design choices and tuning considerations that facilitate its simple and efficient use in drilling applications.publishedVersio

Drillstring Washout Diagnosis Using Friction Estimation and Statistical Change Detection

In oil and gas drilling, corrosion or tensile stress can give small holes in the drillstring, which can cause leakage and prevent sufficient flow of drilling fluid. If such \emph{washout} remains undetected and develops, the consequence can be a complete twist-off of the drillstring. Aiming at early washout diagnosis, this paper employs an adaptive observer to estimate friction parameters in the nonlinear process. Non-Gaussian noise is a nuisance in the parameter estimates, and dedicated generalized likelihood tests are developed to make efficient washout detection with the multivariate $t$-distribution encountered in data. Change detection methods are developed using logged sensor data from a horizontal 1400 m managed pressure drilling test rig. Detection scheme design is conducted using probabilities for false alarm and detection to determine thresholds in hypothesis tests. A multivariate approach is demonstrated to have superior diagnostic properties and is able to diagnose a washout at very low levels. The paper demonstrates the feasibility of fault diagnosis technology in oil and gas drilling

Foreword to the thematic cluster: the Arctic in Rapid Transition — marine ecosystems

The Arctic is warming and losing sea ice. Happening at a much faster rate than previously expected, these changes are causing multiple ecosystem feedbacks in the Arctic Ocean. The Arctic in Rapid Transition (ART) initiative was developed by early-career scientists as an integrative, international, multidisciplinary, long-term pan-Arctic network to study changes and feedbacks among the physical and biogeochemical components of the Arctic Ocean and their ultimate impacts on biological productivity on different timescales. In 2012, ART jointly organized with the Association of Polar Early Career Scientists their second science workshop—Overcoming Challenges of Observation to Model Integration in Marine Ecosystem Response to Sea Ice Transitions—at the Institute of Oceanology, Polish Academy of Sciences, in Sopot. This workshop aimed to identify linkages and feedbacks between atmosphere–ice–ocean forcing and biogeochemical processes, which are critical for ecosystem function, land–ocean interactions and productive capacity of the Arctic Ocean. This special thematic cluster of Polar Research brings together seven papers that grew out of workgroup discussions. Papers examine the climate change impacts on various ecosystem elements, providing important insights on the marine ecological and biogeochemical processes on various timescales. They also highlight priority areas for future research

Fault diagnosis of downhole drilling incidents using adaptive observers and statistical change detection

Downhole abnormal incidents during oil and gas drilling cause costly delays, and may also potentially lead to dangerous scenarios. Different incidents will cause changes to different parts of the physics of the process. Estimating the changes in physical parameters, and correlating these with changes expected from various defects, can be used to diagnose faults while in development. This paper shows how estimated friction parameters and flow rates can be used to detect and isolate the type of incident, as well as isolating the position of a defect. Estimates are shown to be subjected to non-Gaussian, $t$-distributed noise, and a dedicated multivariate statistical change detection approach is used that detects and isolates faults by detecting simultaneous changes in estimated parameters and flow rates. The properties of the multivariate diagnosis method are analyzed, and it is shown how detection and false alarm probabilities are assessed and optimized using data-based learning to obtain thresholds for hypothesis testing. Data from a 1400 m horizontal flow loop is used to test the method, and successful diagnosis of the incidents drillstring washout (pipe leakage), lost circulation, gas influx, and drill bit nozzle plugging are demonstrated

The Environmental Impact of Pig Farming

This study aimed to develop a methodology to evaluate the protection of animals and people from the harmful effects of the farm’s microclimate and environment, taking into consideration the energy, economic and environmental indicators. To achieve this goal, the following were determined for 2019 for the eight countries which are the world leaders in the field of pig farming: the volumes of carbon dioxide pollution, ammonia, dust and manure, and the analytical dependencies between the feed consumption, pig productivity and the concentration of ammonia inside the farm. The weight gain of pigs reduced by 15% with an increase in the concentration of ammonia in the internal air of livestock houses to 20 mg/m3 , but the feed wastage increased by 12%. Mathematical models were developed to estimate the relationships between the feed consumption, pig productivity and the concentration of harmful gas (ammonia) which is one of the main parameters of the microclimate. The results will be used in making technical and technological decisions in the field of microclimate, cleaning and disposal of farm manure. Keywords: pig, farming, ecology, environmen