Christopher E. Morriss

Apparatus including multi-wait time pulsed NMR logging method for determining accurate T2-distributions and accurate T1/T2 ratios and generating a more accurate output record using the updated T2-distributions and T1/T2 ratios

When a pulsed nuclear magnetic resonance (NMR) well logging tool is traversing a wellbore, a NMR well logging method includes magnetizing the hydrogen nuclei in a formation traversed by the tool with a static magnetic field, waiting for a first period of time W1, energizing the formation with oscillating RF pulses, collecting a first plurality of spin echo signals, waiting a second period of time W2 which is different from the first period of time W1, energizing the formation with oscillating RF pulses, collecting a second plurality of spin echo signals, waiting a third period of time W3 which is different from both the second period of time W2 and the first period of time W1, energizing the formation with oscillating RF pulses, collecting a third plurality of spin echo signals, etc. The first, second and third, etc. plurality of spin echo signals corresponding to the different wait times are input to a signal processing apparatus disposed in the tool. Window sums of spin-echo signals are computed and transmitted uphole to a surface oriented signal processing apparatus. In response to the window sums, the surface signal processing apparatus determines an apparent formation T2 -distribution for each wait time in the multi-wait time pulse sequence. The apparent T2 -distributions are used to construct a cost function. When the cost function is minimized, the surface oriented signal processing apparatus determines estimates of the true T1 /T2 ratios and intrinsic T2 -distributions of the formations being logged. The surface signal processing apparatus uses the new T2 -distribution to generate new, more accurate, output record medium.

Application of wavelets in estimating dip angles and conductivities of Earth formation

Earth formations can be modeled as a layered medium with each layer having its own dip angle and conductivity. In a typical exploration environment, a wellbore (about 15 to 30 cms in diameter) is drilled to a depth that may extend to a few kilometers. Formation properties are measured using a sensor that moves along the wellbore trajectory. The sensor is remotely controlled from the surface. Formation resistivity is an important property, which is measured by a sensor consisting of several transmitters and receivers and operating at a frequency of a few MHz. Estimating dip angles provides valuable information in positioning the wellbore trajectory. We present a novel method for estimating dip angles and formation properties using a wavelet-based processing of well log data in conjunction with an inversion method.