Estimating Contamination During Focused Sampling

摘要

Disclosed are methods and apparatus pertaining to processing in-situ, real-time data associated with fluid obtained by a downhole sampling tool. The processing includes generating a population of values for Ĉ, where each value of Ĉ is an estimated value of a fluid property for native formation fluid within the obtained fluid. The obtained data is iteratively fit to a predetermined model in linear space. The model relates the fluid property to pumpout volume or time. Each iterative fitting utilizes a different one of the values for Ĉ. A value Ĉ* is identified as the one of the values for Ĉ that minimizes model fit error in linear space based on the iterative fitting. Selected values for Ĉ that are near Ĉ* are then assessed to determine which one has a minimum integral error of nonlinearity in logarithmic space.

主权项

1. A method comprising:
obtaining in-situ, real-time data associated with fluid obtained by a downhole sampling tool disposed in a borehole that extends into a subterranean formation, wherein the obtained fluid comprises native formation fluid and filtrate contamination resulting from formation of the borehole, wherein the downhole sampling tool is in electrical communication with surface equipment disposed at a wellsite surface from which the borehole extends, and wherein the obtained data includes a plurality of values of a fluid property of the obtained fluid relative to:
a pumpout volume of the fluid pumped from the subterranean formation by the downhole sampling tool; ora pumpout time during which the fluid is pumped from the subterranean formation by the downhole sampling tool; and via operation of at least one of the downhole sampling tool and the surface equipment:
generating a population of values for Ĉ, wherein each value of Ĉ is an estimated value of the fluid property for the native formation fluid;iteratively fitting the obtained data to a predetermined model in linear space, wherein the model relates the fluid property to the pumpout volume or time, and wherein each iterative fitting utilizes a different one of the values for Ĉ;identifying as Ĉ* which one of the values for Ĉ minimizes model fit error in linear space based on the iterative fitting of the obtained data;selecting ones of the values for Ĉ that are near Ĉ*; anddetermining which one of the selected ones of the values for Ĉ near Ĉ* has a minimum integral error of nonlinearity (IEN) in logarithmic space.