In recent years, formation-sampling and formation-testing tools have
provided a variety of new downhole optical measurements for downhole fluid
analysis (DFA). DFA involves an in-situ measurement of optical absorption
spectra used to compute properties such as hydrocarbon composition and gas/oil
ratio (GOR). Abrupt changes in these fluid properties with depth may be markers
for reservoir compartmentalization. However, hydrocarbon differences can be
identified reliably only when the significance of uncertainties from
measurement and the oil-based mud (OBM) filtrate have been taken into account.
Recently, an algorithm called the fluid-comparison algorithm (FCA) was
developed to address this issue.
The FCA propagates uncertainties in optical measurement and contamination
into uncertainties in fluid properties, such as color, composition, and GOR.
The output of the FCA is the probability that two fluids are statistically
different. Real-time application of the FCA can optimize capture of
downhole-fluid samples and generation of a continuous downhole-fluid log
representing the fluid complexity in the reservoir. In addition, by identifying
abrupt changes in fluid properties that occur with depth, the FCA may in some
circumstances be an assay for reservoir compartmentalization.
In this paper, we briefly review the theory of the FCA. The strengths and
limitations of the technique for an improved understanding of reservoir
architecture and fluid complexities are presented in two case studies.
DFA involves the in-situ measurement of optical absorption spectra of
downhole fluids. These spectra are used for fluid identification (oil, water,
and gas phase) and to quantify the level of OBM-filtrate contamination (Mullins
et al. 2000). In addition, optical spectroscopy is invaluable downhole when
determining hydrocarbon composition (e.g., amount of methane, ethane, propane)
and the GOR, a parameter that plays an important role in the design of surface
facilities (Mullins et al. 2005a; Mullins et al. 2005b; Dong et al. 2003;
Fujisawa et al. 2004). GOR is roughly correlated with fluid density:
high-density fluids have a low GOR value, and low-density fluids have a
relatively higher GOR value.
Downhole spectrometers measure optical density (OD), defined as the ratio of
incident light energy to transmitted light energy:
OD = log [Equation]...(1)
Examples of crude-oil and water spectra in the visible and near-infrared
(NIR) regions are shown in Fig. 1. These spectra have three important features.
First, hydrocarbons have a characteristic mode around 1700 nm that is measured
to estimate fluid composition and GOR (Dong et al. 2003). Second, hydrocarbon
spectra show a continuously increasing absorption at shorter wavelengths. This
absorption (or color) is caused by the higher concentration of aromatic
molecules and is typically larger for heavier oils. As a result, high-density
hydrocarbons, which have a larger concentration of aromatic molecules, have a
tan, brown, or black color, while low-density hydrocarbons have little or no
color. Third, the absorption spectrum of water is different from that of crude
oils; this enables one to easily identify and quantify the amount of water in
the tool flowline.
Fluid from the formation flows through a probe into a flowline positioned in
a tool in the wellbore and is assayed by a downhole spectrometer that measures
OD as a function of time and wavelength. At any time instant, the measured OD
is a weighted linear combination of the spectra of the undesired OBM filtrate
and the desired formation fluid. Initially, the measured spectra are dominated
by the OBM filtrate. With increased pumping time, the amount of OBM filtrate
diminishes. Thus, at later times, the measured OD is dominated by the native
formation fluid. The process wherein the measured OD asymptotically reflects
the spectrum of the formation fluid is referred to as the “cleanup” process.
Because of downhole-hardware limitations, the absorption spectrum is measured
at only a few discrete wavelengths (also referred to as channels). These
channels are distributed from the visible region into the NIR region. The
channels in the visible region are referred to as "color channels,"
while the channels in the NIR region are referred to as "NIR
A typical example of time-series data obtained as fluid flows past the
downhole spectrometer is shown in Fig. 2a. The different traces correspond to
the different channels. The volumetric level of OBM-filtrate contamination is
predicted by monitoring one of the channels that clearly distinguishes mud
filtrate from formation hydrocarbon. If the hydrocarbon is heavy (e.g., dark
oil), the mud filtrate (assumed colorless) is discriminated from the formation
fluid by monitoring the time evolution of OD in one of the color channels. If
the hydrocarbon is light (e.g., gas or volatile oil), the mud filtrate (assumed
to have no methane) is discriminated from the formation fluid using the time
evolution of an NIR channel sensitive to the amount of methane (Fujisawa et al.
© 2008. Society of Petroleum Engineers
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- Original manuscript received:
2 June 2006
- Meeting paper published:
11 September 2006
- Revised manuscript received:
26 October 2007
- Manuscript approved:
1 November 2007
- Version of record:
20 June 2008