Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Earth science
Reexamination Certificate
2003-01-08
2004-06-15
McElheny, Jr., Donald (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Earth science
C702S007000, C702S008000
Reexamination Certificate
active
06751557
ABSTRACT:
BACKGROUND OF THE INVENTION
The subject matter of the present invention relates to a method and apparatus for generating a first plurality of rock classifications corresponding to a plurality of dry weight outputs from a well logging tool adapted to be disposed in a wellbore in response to a Ternary Model Diagram and a corresponding established rule base and for generating an output log including a second plurality of rock classifications as a function of depth in the wellbore, the second plurality of rock classifications being refined relative to the first plurality of rock classifications.
It has always been a challenge to Petroleum Geologists worldwide to find a means to examine and understand the geological characteristics of subsurface lithologic formations. Technological advances in the industry have made it possible to acquire measurements of the physics of the subsurface rocks and even provide images of the subsurface borehole geology. Sensors and tools are now available that provide the ability to not only obtain a high resolution image of the borehole but also allow for structural and stratigraphic interpretation, including thin-bed detection, compartmentalization, high-resolution net-pay calculation and well correlation. Another very useful tool sensor is a borehole spectroscopy tool. This tool provides the general elemental composition of the rock and its quantitative geochemical lithology. This data adds value to the geoscience disciplines including geology, geophysics, petrophysics, reservoir engineering, and production engineering, since the total QFM, the total clay content and the total carbonate fractions are accurately estimated (the term ‘QFM’ indicating Quartz, Feldspar, and Mica). However, studies based solely on borehole images or only on borehole spectroscopy data are not able to provide comprehensive subsurface geological description and interpretation solutions. Images alone cannot distinguish wet sand from shale, or a calcareous (limy) streak from a thin hydrocarbon rich sand bed. Spectroscopy outputs alone cannot resolve small geological features, such as thin sand beds.
As a result, a need exists which: (1) will address the aforementioned problems, (2) will use the strengths of the spectroscopy tools in general, (3) will use the strengths of both the borehole imaging tools and the spectroscopy tools in particular, and (4) will further enhance subsurface geological description and interpretation.
SUMMARY OF THE INVENTION
A first rock classification method and apparatus, which represents a first rock classification system, has been developed to classify rocks in response to a set of spectroscopy data from an Elemental Capture Spectroscopy Sonde and to generate a resulting output that will improve subsurface geological interpretation including reservoir characterization. The resulting output of this first rock classification system (i.e., a plurality of rock classifications corresponding, respectively, to a plurality of data points in the spectroscopy data) is used by an additional more refined rock classification system called ‘iCore’.
In addition, a second rock classification method and apparatus, which represents a second rock classification system, has been developed which will merge the data obtained from two kinds of borehole measurement devices [i.e., the Elemental Capture Spectroscopy Sonde and the Oil Based Mud Imaging (OBMI) Sonde] and will use the rock classification system of the first rock classification system to provide a second resulting output that will improve subsurface geological interpretation including reservoir characterization. The second resulting output of this second rock classification system is a well log representing a refined rock classification system called the ‘iCore lithofacies’ log or the ‘iCore’ rock classification log.
The first rock classification system involves the use of a Ternary Diagram (TD) Model. The Ternary Diagram Model, or TD model, is a triangularly shaped model having three axes, WCAR representing the percent dry weight of total Carbonate, WSAN representing the percent dry weight of total QFM, and WCLA representing the percent dry weight of total Clay. The TD model includes twelve (12) rock classifications having specific enclosed boundaries in the TD model: marl, pelagic shale, shale, sandy shale, shaly sand, sand, clean sand, calcareous sand, calcareous shale, carbonate, sandy carbonate, and shaly carbonate. Since each of the twelve rock classifications in the TD model have specific enclosed boundaries, those enclosed boundaries are defined by certain percentages of dry weight on each of the three WCAR, WSAN, and WCLA axes. As a result, those enclosed boundaries in the TD model will define a set of rules which are hereinafter called the ‘rule base’. The rule base, shown in
FIG. 3
, defines marl, for example, as having a percent dry weight of total Clay on the WCLA axis as being greater then or equal to 0.35 and less than or equal to 0.65 and a percent dry weight of total Carbonate on the WCAR axis as being greater than or equal to 0.35 and less than or equal to 0.65. Similarly, the rule base defines pelagic shale as having a percent dry weight of total Clay on the WCLA axis as being greater than or equal to 0.7. In
FIG. 3
, the rule base also has a specific definition (in terms of percent dry weight of total QFM or total Clay or total Carbonate) for shale, sandy shale, shaly sand, sand, clean sand, calcareous sand, calcareous shale, carbonate, sandy carbonate, and shaly carbonate. A computer, workstation or personal computer stores the rule base and a rock classification software. The computer is responsive to certain data points which are generated by a well logging tool known as the Elemental Capture Spectroscopy Sonde (ECS) which is owned and operated by Schlumberger Technology Corporation of Houston, Tex. The data points each comprise a percent dry weight of total carbonate, total QFM, and total clay. The computer process will compare each data point with each of the rules in the rule base, and, when a match is found, a specific rock classification for that data point is generated. When a plurality of data points are input to the computer, a corresponding plurality of rock classifications are generated. As a result, the first rock classification system uses the Ternary Diagram Model, and the rule base generated therefrom, to produce a plurality of rock classifications for each of the data points generated by the ECS well logging tool.
The second rock classification system involves the use of a second rule base and the aforementioned Ternary Diagram Model stored in the memory of a computer, workstation or personal computer. Another well logging tool known as the Oil Based Mud Imaging (OBMI) Sonde generates four tracks as a function of depth in a wellbore representative of an Earth formation inside the wellbore, the four tracks corresponding to four pads on the OBMI Sonde. The computer receives ‘three sets of input data’: (1) the four tracks as a function of depth that is output from the OBMI Sonde, (2) the certain data points generated by the Elemental Capture Spectroscopy Sonde where each data point comprises a percent dry weight of total carbonate, total QFM, and total clay, and (3) the rule base associated with the Ternary Diagram Model. In response to the ‘three sets of input data’, the second rule base stored in the computer will generate an output ‘log’ which is hereinafter called a ‘Refined Lithofacies’ or ‘iCore Lithofacies’ or ‘iCore rock classification’. The ‘iCore Lithofacies’ output is a ‘log’, and that ‘log’ includes a first part which was previously present on that log: an output from the ECS sonde, a quality control track from the OBMI sonde, and the four tracks as a function of depth from the OBMI sonde. However, that ‘log’ also includes a new and novel second part: an ‘iCore’ rock classification (otherwise known as a ‘Refined Lithofacies’ or an ‘iCore lithofacies’) section as a function of depth. For each depth on the ‘log’, a color and/or symbol can be seen on the ‘
Kear George Richard
Kumar Anish
Shehab Gamal
Viloria Oswaldo E.
Williamson David
Brigitte L. Jeffery, John Ryberg
McElheny Jr. Donald
Schlumberger Technology Corporation
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