Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Earth science
Reexamination Certificate
2000-01-19
2001-09-11
McElheny, Jr., Donald E. (Department: 2862)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Earth science
Reexamination Certificate
active
06289283
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates generally to investigation of subsurface earth formations, and, more particularly, to a method for correcting data obtained by a downhole tool for anomalies that may be caused by factors including environmental characteristics and/or intrinsic tool parameters. The invention has general application in the well logging art, but is particularly useful at a well site while logging.
2. Description of Related Art
A major goal of well logging is to maximize the amount of hydrocarbons recovered from an earth formation. By continuously monitoring oil saturation in the earth formation, secondary and tertiary techniques may be employed to enhance recovery of hydrocarbons. Oil saturation is usually expressed as a percentage by volume of oil in the pore space. Different methods have been developed for monitoring oil saturation during production of a well.
One method for monitoring oil saturation is based on the fact that hydrocarbons contain carbon and water contains oxygen. A carbon/oxygen ratio (“COR”) is used to compute oil saturation. The COR may be derived by applying a spectral fitting technique to an inelastic gamma ray spectrum to compute carbon, oxygen, and other elements present in the formation. This approach provides one means for computing the COR.
Alternatively, the COR may be derived using counts from broad energy regions “windows” in the inelastic gamma ray spectrum across the region of the predominant carbon and oxygen gamma ray energies. The COR is derived by taking the ratio of the counting-rates in two energy windows of the inelastic gamma ray spectrum. Such measurements will be referred to herein as “windows COR value” measurements.
All gamma rays in these windows do not result solely from the elements carbon (C) and oxygen (O). Nevertheless, this count-rate windows COR value will respond to changes in oil saturation in the formation, provided the other formation and borehole properties remain constant. The conversion between the windows COR value and the oil-saturation value is typically determined by making many measurements with one tool (called the “database” or “characterization” tool) at standard conditions in laboratory simulated formations having accurately known porosity, lithology, completion geometry, and saturation. This database set of measurements is commonly known as the “tool characterization.” The tool characterization may also be derived by theoretical modeling techniques as known in the art.
Gamma ray photon energies are detected downhole with the use of conventional downhole tools, also known as spectrometers, such as those disclosed in U.S. Pat. No. 4,937,446 to McKeon et al. (assigned to the present assignee). The '446 patent is hereby incorporated in its entirety by reference herein. The '446 patent discloses a downhole tool for determining hydrocarbon or fluid saturations within a formation adjacent a well bore. One or more gamma ray detectors on the downhole tool measure gamma ray photons produced from carbon and oxygen during the neutron burst as a result of neutron inelastic scattering from the nuclei of carbon and oxygen present in the formation and the borehole. Analyzing the inelastically produced gamma ray photon energy spectrum for the characteristic energy gamma ray photons from atomic elements such as carbon (C), oxygen (O), silicon (Si), calcium (Ca), iron (Fe), and the like, allows the presence of these elements, and their relative abundance, in the formation and borehole regions, to be quantified.
When the formation water salinity is known and is higher than about 20000 parts per million (20 kppm) sodium chloride (NaCl), a different pulsed-neutron technique may be used to measure the rate of capture of thermal neutrons. This quantity, known as the thermal-neutron capture cross-section (Sigma), is strongly influenced by the affinity of chlorine (Cl), a primary constituent of saltwater, to absorb thermal neutrons. Conventional pulsed-neutron tools measure Sigma by measuring the counting rate of gamma ray photons produced by thermal neutron capture after a pulse of neutrons has been released into the formation.
FIG. 1
shows a typical laboratory formation inelastic gamma ray spectrum
100
, containing carbon peaks
110
and
120
, in the carbon window region
130
, and oxygen peaks
140
,
150
and
160
, in the oxygen window region
170
. The gamma ray energies (corresponding to channel numbers) are plotted along the horizontal axis, and the detector counting rates are plotted on a logarithmic scale along the vertical axis.
FIG. 2
shows a typical windows COR value response-graph
200
(a characterization in a specific formation and completion geometry) plotted against porosity and formation oil-saturation. The formation porosity (in percentage units, p.u., the percentage by volume of the formation that is filled with fluids such as air, gas or liquid) is plotted along the horizontal axis, and the windows COR value (dimensionless ratio of respective counts) is plotted along the vertical axis. Clearly, for any given porosity, there is a COR-based formation oil response bounded by the water-saturated line
210
(on the bottom) and the oil-saturated line
220
(on the top). This windows COR value response-graph
200
is commonly referred to as the “windows COR value fan chart” and forms the basis for windows COR value interpretation.
Detectors in downhole tools used to obtain the data to calculate the windows COR value typically use scintillation crystals, such as thallium-activated sodium iodide (NaI), thallium-activated or sodium-activated cesium iodide, bismuth germanate (BGO), gadolinium oxyorthosilicate doped with cerium (GSO), and the like. These scintillation detectors typically all have the undesirable characteristic of losing pulse-height resolution with increasing temperature, resulting in spectral degradation. This means that spectral peaks that are relatively “sharp” and well defined at room temperature will generally degrade (broaden) when the detector gets hot. For example,
FIG. 3
shows the effects of temperature on a sample laboratory formation inelastic spectrum
300
(shown in phantom) superimposed on the typical laboratory formation inelastic gamma ray spectrum
100
, as shown in FIG.
1
.
In addition, not all gamma ray detectors will have the same inherent or so-called “intrinsic” resolution even at room temperature. As a scintillation detector heats up, the detector resolution typically worsens and the carbon and oxygen peaks broaden, resulting in a net “spillover” or loss of counts from both the carbon and oxygen windows. For example, in
FIG. 3
, note the increase of count-rate in an intermediate region
310
between the oxygen window
130
and the carbon window
170
, as counts from both the nearby oxygen peak
140
and the carbon peak
120
“spill over” into this intermediate region
310
. Unfortunately, the carbon window
130
and oxygen window
170
count-rates do not both change by the same percentage, and this results in a net bias in the windows COR value. Typically, the windows COR value generally tends to increase with worsening resolution.
In summary, the measured windows COR value of a given tool will generally vary with temperature, all other parameters of the formation and borehole remaining constant. Consequently, the measured windows COR value of a given tool will generally give an erroneous oil-saturation reading when hot. In addition, a tool having a worse intrinsic resolution than the tool used in the laboratory or database characterizations will also give an erroneous oil-saturation reading, even at room temperature.
FIG. 4
shows, using laboratory formation data, for example, how resolution degradation can affect the windows COR value readings. Note that the effect of resolution degradation, moves the points on a degraded fan curve
400
(outlined in phantom) characterization, considerably off a correct tool fan curve
410
characterization, moving the degraded fan curve
400
characterization to a position
McElheny Jr. Donald E.
Ryberg John J.
Schlumberger Technology Corporation
Segura Victor H.
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