Bruno Luong

Optimal control technique for magnet design in inside-out nuclear magnetic resonance

The magnets used in a family of inside-out nuclear magnetic resonance (NMR) well-logging tools usually consist of several segments of magnet materials, with each segment magnetized differently. In a tool, the magnet is surrounded with a nonlinear magnetic material, such as ferrite or steel, that is primarily used in the RF coil or in shielding the electronic components from strong magnetic fields. The main objective of the tool design is to find a set of magnetization vectors that result in a desired magnetic field profile in a particular region. A typical nonlinear finite-element method (FEM) model of such a design has about quarter of a million unknowns and requires about 35 h of processor time on a Sun Ultra 60 296-MHz machine with 1 GB of RAM. It generally requires many executions of the nonlinear FEM to arrive at a satisfactory design. In this paper, an optimal control technique in conjunction with FEM is proposed to speed up the design process. A magnet built from the design showed excellent agreement between the measured and computed data and validated the numerical method.

Analysis and optimization of NMR sensor for oilfield exploration applications

Nuclear magnetic resonance (NMR) measurements have become an important part of oilfield well-logging to identify and quantify oil and gas reservoirs. In this paper, some design aspects of NMR sensor for well-logging applications are discussed. The RF and static magnetic fields are computed using a 3D finite element method (FEM). A perturbation technique along with FEM is used to evaluate the power loss in conductors that avoids the need for small discretization steps along the conductor thickness. The magnet is built by stacking several magnet segments along the axial direction and the objective is to magnetize and shape these segments in such a way so as to produce a desired field profile in front of the magnet. An optimal control technique is used in conjunction with the FEM to speed up the design process with signal-to-noise ratio, frequency of operations, depth of investigation, and prepolarization time being the optimization constraints. Very good agreement between the measured and computed antenna efficiency and magnetic field is obtained thus validating the numerical model.