Determination of True Formation Resistivity from LWD Conventional Resistivity Measurements in a Horizontal Well

摘要

In a horizontal well, apparent resistivity curves often show varied separations and increased values due to the polarization horn effects near a boundary and other effects such as adjacent beds or anisotropy. The true formation resistivity (Rt) is uncertain and can be mis-interpreted. As a consequence, saturation estimates are uncertain so that the reserves cannot be accurately predicted. A full inversion can be used to derive the true Rt. However, the instability of an inversion due to the lack of measurement variation along the measured depth makes the Rt derivation very challenging. To determine a true Rt from the logging-while-drilling (LWD) resistivity measurements, a general full inversion is usually time-consuming and needs some inputs on formation model. This paper presents an alternative approach to derive the true Rt without input of any prior information. The alternative approach uses a simple two-layer model for the removal of horn effects and derives a solution at two steps: a) inverting resistivities of the two layers at each distance away from the boundary; b) selecting a solution with specific constraints such as using statistics in a moving window and internally consistent physical constraints to make the solution more reliable. In the first step, neural networks are developed to calculate tool responses and derivatives for the savings of computation time and memory needs. Synthetic examples show that true Rt can be recovered when the relative dip between a borehole and a layered formation is greater than 85 degrees. The examples show that bed boundaries can be reproduced with sufficient accuracy by our approach, among others to define pay zone intervals. In addition, the resolution of the method was studied with models of different layer thicknesses and is discussed in details in the paper. As an outcome, the derived true Rt reads lower in a resistive thinner layer and reads slightly higher in a conductive thinner layer. A field example from a North Sea oil field demonstrates very promising and robust Rt results from the method. The inversion is fully automatic and can be used in real time and downhole. Physical constraints that are special to a horizontal well and better strategies make our algorithm robust and very fast.