Development of a Novel Hybrid-Type Rotary Steerable System for Directional Drilling
Unlike conventional resources, unconventional resources, such as shale gas and coal bed methane, are situated horizontally under geological formations. To exploit these resources, directional drilling and hydraulic fracturing technologies are required. In directional drilling, the dog leg severity (DLS), which indicates how much the angle changes while drilling 100 ft, is a major issue with respect to the cost and time of drilling. In this paper, we briefly review different types of directional drilling methods and propose a new hybrid-type rotary steerable system (RSS). DLS calculations based on three-point geometry for these systems are suggested. This hybrid RSS combining two conventional types of RSSs: point-the-bit and push-the-bit systems, achieves better steerability. The hybrid mechanism is implemented using hybrid pads with hydraulic cylinders and a spherical joint. The advantages of the proposed system are demonstrated by performing small-scale prototype and cement block drilling tests.
A Self-Optimizing Control System for Hard Rock Percussive Drilling
The derivation and application of a self-optimizing control system for percussive drilling of hard rock is presented. The control system superimposes an oscillating force signal onto the drill feed force and demodulates the signal from the drill rotational torque. The resultant demodulated signal is then used to control the drill, allowing real-time maximization of penetration rate, minimum hole deviation, and measurement of rock characteristics regardless of drilling conditions. The control system allows the drill to adapt to changing rock conditions. Testing has proven the control to be reliable and to increase drilling efficiency.
An operational method for estimating signal to noise ratios from data acquired with imaging spectrometers
A method, using the concept of local means and local standard deviations of small imaging blocks and using a box counting procedure, has been developed for unsupervised estimation of the average signal to noise ratios of images in which the noise is additive. The method has been applied to simulated images with Gaussian noise, to images acquired with the Airborne Visible Infrared Imaging Spectrometer and with the Geophysical and Environmental Research Imaging Spectrometer. The method is compared with other techniques for estimating signal to noise ratios from imaging data. It is believed that the method is generally applicable to images having many small homogeneous blocks. Because the method does not take into account interband effects, it is not appropriate to use the method to estimate signal to noise ratios from images having nonnegligible interband radiometric calibration errors at spatial scales less than or equal to the size of the small imaging blocks used in the noise estimation.