3-D Well Log Invention

Abstract

In an embodiment, creation of a continuous three dimensional array of data from digital information obtained from a wellbore, and representation in a seismic data formatted dataset. In an embodiment, providing the capability to export stratigraphic interpretations made while working within the 3D-log data volume back to any wellbore that is encompassed within the areal extent of the 3D-log data volume. In one embodiment, a 2D well grid creation process comprises the steps of (a) selecting an initial grid spacing, (b) assigning wells from a dataset of well data to closest nodes in the grid, (c) if a plurality of wells are assigned to a single node after completing step (b), narrowing the grid spacing and repeating step (b) until no more than one well is assigned to any node. In an embodiment the non-well nodes are populated by extrapolating from adjacent single well nodes.

Description

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of co-pending U.S. Ser. No. 12/911,272 filed Oct. 25, 2010, now U.S. Pat. No. 8,694,261 which is a non-provisional of U.S. Pat. No. 61/313,211, filed Mar. 22, 2010.

BACKGROUND

The term “pseudo-seismic” has been used to describe efforts to convert any non-seismic data type into the seismic data domain. Previous workers converted digital well-log data into SEG-Y format and loaded those data into seismic workstations. The results were less than acceptable because of the discontinuous nature of wellbore data and the fact that the method destroyed the connection between the actual wellbore location and the location of the trace to which it has been assigned. See Carr et al., 2-D and 3-D Pseudo-Seismic Transforms of Wireline Logs: A Seismic Approach to Petrophysical Sequence Stratigraphy, Open-File Reports, Kansas Geological Survey, University of Kansas (1995) (available at http://www.kgs.ku.edu/PRS/publication/carr.html); Escaloma et al., Sequence Stratigraphic analysis of Eocene clastic foreland deposits in central Lake Maracaibo using high-resolution well correlation and 3-D seismic data., AAPG Bulletin, V. 90, No. 4, pp. 581-623 (April 2006).

For example, previous workers also calibrated seismic attribute data with wellbore data to generate pseudo-well logs to predict the nature of rocks at a given location. The method used 3D-seismic attribute data as input to derive expected values of standard well log curves at a single location, which may be a wellbore or a hypothetical wellbore location. For example, see U.S. Pat. No. 7,706,981.

Denham and Nelson, Rock Property Data Volumes from Well Logs, Search and Discovery Article #40268 (2007), generated rock property data in 60 meter vertical sample intervals for wellbores and loaded these data into a regular grid. The values of the grid nodes were averaged based upon the proximity of the wellbores selected within a given radius of the wellbore. They concluded that the technique was suitable for regional analysis only.

U.S. Pat. No. 7,054,753 discloses a method of locating oil and gas exploration prospects by data visualization and organization by digitizing well log data, marking common geologic time markers and visually displaying the data in various viewing formats.

All references mentioned herein are hereby incorporated herein by reference in their entireties for all purposes.

SUMMARY OF THE INVENTION

The present invention relates in one aspect to the creation of a continuous three dimensional array of data derived from digital information obtained from various depths within a wellbore, and the representation of these data in a formatted dataset that can be manipulated in standard 3D-seismic interpretation and visualization software. The invention also relates in another aspect to providing the capability to export stratigraphic interpretations made while working within the 3D-log data volume back to any wellbore that is encompassed within the areal extent of the 3D-log data volume.

In one embodiment, a 2D well grid creation process comprises the steps of (a) selecting an initial grid spacing, (b) assigning wells from a dataset of well data to closest nodes in the grid, (c) if a plurality of wells are assigned to a single node after completing step (b), narrowing the grid spacing and repeating step (b) until no more than one well is assigned to any node.

In another embodiment, a 3D well log grid creation process comprises the step of associating tabulated well log data with a matrix of grid nodes with single wells assigned to single nodes. In a further embodiment, the tabulated well log data can comprise stratigraphic correlations by well, whereby the 3D well log grid comprises a matrix of grid nodes with stratigraphic correlations assigned to the single-well nodes. Further still, in an embodiment the process can include populating non-well nodes with stratigraphic correlation data.

In an embodiment, the 3D well log grid creation process can include populating non-well nodes with well log data extrapolated from single-well nodes. Further, in one embodiment stratigraphic tops are used to control the non-well node population. In one embodiment, the all-node-populated 3D matrix of well log data is converted to a seismic data format such as, for example, SEG-Y, SEG P1, as defined by the Society of Exploration Geophysics (SEG), and so on. The 3D well log dataset can be interpreted using standard seismic industry software, e.g., petrophysical, log facies, structural and other interpretations; further the interpretations can be associated with a well process at a specific well through the use of unique well identifiers, e.g., completion and production of oil and gas wells, the creation of pseudo wells to evaluate exploration opportunities, and the like.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic overview of a 3D well log data process according to an embodiment of the invention.

FIG. 2 is a schematic diagram of a general well data collection process according to an embodiment of the invention.

FIG. 3 is a schematic diagram of a well log data collection process according to an embodiment of the invention.

FIG. 4 is a schematic diagram of a 2D well grid creation process according to an embodiment of the invention.

FIG. 5 is a schematic diagram of a 3D well grid creation process according to an embodiment of the invention.

FIG. 6 is a schematic diagram of an alternative 3D well grid creation process involving stratigraphic correlations according to an embodiment of the invention.

FIG. 7 is a schematic diagram of a process to populate non-well grid nodes according to an embodiment of the invention.

FIG. 8 is a schematic diagram showing conversion of a 3D well grid into a standard seismic data format according to an embodiment of the invention.

FIG. 9 is a schematic diagram of interpretation of 3D log dataset in standard seismic data format using standard industry software according to an embodiment of the invention.

FIG. 10 is a schematic diagram of a process to associate the interpretations of FIG. 9 with specific wells (or pseudo-wells) according to an embodiment of the invention.

FIG. 11 is a plan diagram of the location of hypothetical wells W1, W2, W3 and W4 associated with well log data according to an embodiment of the invention as described in the examples below.

FIG. 12 is a plan diagram of the wells of FIG. 11 with an initial grid system applied according to an embodiment of the invention as described in the examples below.

FIG. 13 is a plan diagram of the wells and grid of FIG. 12 showing association of the wells to the nearest grid node according to an embodiment of the invention as described in the examples below, wherein more than one well is associated with a grid node.

FIG. 14 is a plan diagram of the wells of FIGS. 11 to 13 following reduction (halving) of the grid spacing from FIG. 12 showing association of the wells to the nearest grid node according to an embodiment of the invention as described in the examples below, wherein no more than one well is associated with any grid node.

FIG. 15 is a plan diagram of hypothetical wells W1, W2 showing assignment to grid nodes according to an embodiment of the invention as described in the examples below.

FIG. 16 shows a generalized well log for well W1 of FIG. 15 with stratigraphic correlations A and B according to an embodiment of the invention as described in the examples below.

FIG. 17 shows a generalized well log for well W2 of FIG. 15 with stratigraphic correlations A and B according to an embodiment of the invention as described in the examples below.

FIG. 18 shows a generated well log for node GN(1,1) of FIG. 15 by mathematical averaging without applying stratigraphic correlations according to an embodiment of the invention as described in the examples below.

FIG. 19 shows a generated well log for node GN(1,1) of FIG. 15 by applying stratigraphic correlations according to an embodiment of the invention as described in the examples below.

FIG. 20 shows a wiggle trace display of ten well log gamma-ray curves converted into SEG-Y format according to the process shown in FIG. 8.

FIG. 21 shows the data shown in FIG. 20 in a commercially available 3D seismic evaluation application.

DESCRIPTION OF THE INVENTION

With reference to FIG. 1, the 3D-log process according to one embodiment of the invention provides a means to take depth dependent measurements from a randomly spaced collection of wellbores and create a continuous volume of data that can be loaded into software designed to interpret and visualize a 3D-Seismic dataset.

One embodiment shown in FIGS. 2 and 3 utilizes digital wellbore data as input. Examples can include geophysical well-log curves 210 collected from wire-line logging of wellbores, core analyses performed on cores collected during drilling of wells, and virtually any other data attribute that can be quantified and associated with a depth within a wellbore.

The reference elevation 130 (FIG. 2), i.e., the elevation above mean sea level from which borehole measurements are taken, of each wellbore to be used, in one embodiment is available to the process.

In an embodiment, in step 310 (FIG. 4) a uniform grid with constant spacing between nodes is superimposed over an area that encompasses all wellbores to be used. Common grid node spacings can be from 10 to 100 meters, but smaller or larger spacings can be used if desired. In one embodiment, a uniform grid spacing can include spacing that can be the same or different with respect to the X- and Y-axes, e.g. a relatively larger spacing along one axis than the other.

In an embodiment, each wellbore can have a unique identifier carried as an attribute of the node nearest to its actual location. This unique identifier can be the American Petroleum Institute (API) identifier or any other suitable identifier.

In an embodiment, no two wellbores can be assigned to the same grid node. The grid spacing can be reduced in an iterative process in one embodiment, or one of the wellbores can be moved to the next nearest available node in an alternative or additional embodiment.

In an embodiment, utilizing an algorithm of triangulation, each grid node that has not been assigned to an actual wellbore will have calculated a weighting function based upon the distance between it and all grid nodes with assigned data, which will be kept in an array for reference within the processing according to the following equation:

GN_(O,n)=DF/f(DN)

where GN is the array of grid nodes containing the weighting function values; DF is a weighting constant that can be allocated prior to processing; f(DN) is a function that can be allocated prior to processing, allowing flexibility in determining, for example, whether a linear or exponential data relationship exists between the grid nodes; and DN is the distance between the grid node being evaluated and a grid node with an assigned well.

According to an embodiment, a data value can be determined for each depth increment at each wellbore by using the gridnode (GN) values calculated, and performing a summation of all wellbore data at the same measured depth multiplied by the respective GN value for wells within a defined search radius.

In an embodiment, the results can be assigned to a trace array for each bin.

As shown in FIG. 8, SEGY files are generated for the 3D-log survey.

After interpretation in any standard exploration workstation according to the embodiment of FIGS. 9 and 10, the interpretations are output and reformatted for loading into well databases and interpretation systems.

Accordingly, the invention provides the following embodiments:

• • A. A process to create a 2D well grid, comprising the steps of:
    • a. selecting an initial 2D grid spacing,
    • b. assigning wells from a dataset of well data to closest nodes in the grid, and
    • c. if a plurality of wells are assigned to a single node after completing step b, narrowing the grid spacing and repeating step b until no more than one well is assigned to any node.
  • B. A process to create a 3D well log grid, comprising the step of associating tabulated well log data with a matrix of grid nodes wherein single wells are assigned to single nodes to generate a 3D well log grid.
  • C. The process of Embodiment B comprising generating the matrix of grid nodes by the steps of:
    • a. selecting an initial 2D grid spacing,
    • b. assigning wells from a dataset of well data to closest nodes in the grid, and
    • c. if a plurality of wells are assigned to a single node after completing step b, narrowing the grid spacing and repeating step b until no more than one well is assigned to any node.
  • D. The process of Embodiments B or C wherein the tabulated well log data comprise stratigraphic correlations by well, whereby the 3D well log grid comprises a matrix of grid nodes with stratigraphic correlations assigned to the single-well nodes.
  • E. The process of any one of Embodiments A, B, C, or D, further comprising populating non-well nodes with stratigraphic correlation data.
  • F. The process of any one of Embodiments A, B, C, D, or E, further comprising populating non-well nodes with well log data extrapolated from single-well nodes.
  • G. The process of Embodiments E or F, wherein stratigraphic tops are used to control the non-well node population.
  • H. The process of any one of Embodiments E, F, or G, further comprising converting the all-node-populated 3D matrix of well log data to a seismic data format.
  • I. The process of Embodiment H, wherein the seismic data format comprises SEG-Y or SEG P1.
  • J. The process of Embodiments H or I, further comprising interpreting the seismic data formatted 3D matrix.
  • K. The process of Embodiment J, wherein the interpretation is selected from petrophysical, log facies, structural and combinations thereof.
  • L. The process of Embodiments J or K, further comprising associating the interpretations with a well process at a specific well through the use of unique well identifiers.
  • M. The process of Embodiment L, wherein the well process comprises completion or production of oil and gas wells.
  • N. The process of Embodiment L, wherein the well process comprises the creation of pseudo wells to evaluate exploration opportunities.

EXAMPLES

As an example of establishing a single-well, single-node two-dimensional grid, a process according to one embodiment of the invention is applied to hypothetical wells W1, W2, W3 and W4 as shown in FIG. 11. An initial grid is applied with grid nodes GN(0,0) through GN(2,2) as shown in FIG. 12. Next, as shown in FIG. 13, the wells are associated with the closest node, i.e. W1 with GN(0,0), W2 with GN(1,1), W3 with GN(1,1), and W4 with GN(1,2). However, two wells (W2, W3) are associated with GN(1,1), so the grid spacing is reduced, e.g., halved as shown in FIG. 14. In this spacing, the wells are again associated with the closest node, i.e. W1 with GN(0,0), W2 with GN(3,1), W3 with GN(2,2), and W4 with GN(2,4). This grid spacing is suitable because no more than one well is associated with any single node.

As an example of populating non-well nodes, a process according to two different embodiments of the invention is applied to GN(1,1), which is between GN(0,1) and GN(2,1) to which are assigned wells W1 and W2, respectively, as shown in FIG. 15. The generalized well logs for wells W1 and W2, respectively, shown in FIGS. 16 and 17, have stratigraphic correlations A and B with the relationship between depth, Y, and a generalized logging variable X, as follows: over the intervals Y=0→A, X=2; over the intervals Y=A→B, X=1; and over the intervals Y=B→1000, X=3.

In one embodiment where stratigraphic correlations A and B are not used, a mathematical average of the well logging variable for the nearby wells is applied as shown in FIG. 18. In this instance the generalized well log for node GN(1,1) is as follows: over the interval Y=0→A1, X=2; over the interval Y=A1→A2, X=1.5; over the interval Y=A2→B1, X=2; over the interval Y=B1→B2, X=2; and over the interval Y=B2→1000, X=3; where A1 and B1 represent the depth of the stratigraphic correlations at well W1, and A2 and B2 at well W2. This approach tends to blur the well log data for the non-well node being populated across the stratigraphic correlations, but is still useful in one embodiment.

The use of stratigraphic correlations for the same node is illustrated in FIG. 19. In this instance, the height of the correlations A and B at GN(1,1) is taken as a weighted average of the heights of the same correlations at the nearby wells W1 and W2, e.g., A(1,1)=(A1+A2)/2 and B(1,1)=(B1+B2)/2. This provides a more realistic population of the well log data at the non-well nodes, and a more crisp visualization of the data at the stratigraphic correlations that can be expected.

As is illustrated in FIG. 20, well log data, in this case ten well log gamma-ray curves have been converted into SEG-Y format according to an embodiment of the instant disclosure. The data are shown in a “wiggle trace” display as are readily known to one of minimal skill in the art. FIG. 21 shows the data presented in FIG. 20, presented in a 3D seismic application (OpendTect V.4.0), which is commercially available and readily known to one of skill in the art. As FIGS. 20 and 21. demonstrate, the data produced according to the processes disclosed herein may be interpreted, processed, and manipulated just like seismic data generated from traditional sources.

All documents described herein are incorporated by reference herein, including any patent applications and/or testing procedures to the extent that they are not inconsistent with this application and claims. The principles, preferred embodiments, and modes of operation of the present invention have been described in the foregoing specification. Although the invention herein has been described with reference to particular embodiments, it is to be understood that these embodiments are merely illustrative of the principles and applications of the present invention. It is therefore to be understood that numerous modifications may be made to the illustrative embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims.

Claims

1. A process to create a 2D well grid comprising the steps of:

a. selecting an initial 2D grid spacing,

b. assigning wells from a dataset of well data to closest nodes in the grid, and

c. if a plurality of wells are assigned to a single node after completing step b, narrowing the grid spacing and repeating step b until no more than one well is assigned to any node.

2. A process to create a 3D well log grid, comprising the step of associating tabulated well log data with a matrix of grid nodes wherein single wells are assigned to single nodes to generate a 3D well log grid.

3. The process of claim 2 comprising generating the matrix of grid nodes by the steps of:

a. selecting an initial 2D grid spacing,

b. assigning wells from a dataset of well data to closest nodes in the grid, and

c. if a plurality of wells are assigned to a single node after completing step b, narrowing the grid spacing and repeating step b until no more than one well is assigned to any node.

4. The process of claim 3 wherein the tabulated well log data comprise stratigraphic correlations by well, whereby the 3D well log grid comprises a matrix of grid nodes with stratigraphic correlations assigned to the single-well nodes.

5. The process of claim 1, further comprising populating non-well nodes with stratigraphic correlation data.

6. The process of claim 3, further comprising populating non-well nodes with stratigraphic correlation data.

7. The process of claim 1, further comprising populating non-well nodes with well log data extrapolated from single-well nodes.

8. The process of claim 3, further comprising populating non-well nodes with well log data extrapolated from single-well nodes.

9. The process of claim 5 wherein stratigraphic tops are used to control the non-well node population.

10. The process of claim 6 wherein stratigraphic tops are used to control the non-well node population.

11. The process of claim 2 further comprising converting the all-node-populated 3D matrix of well log data to a seismic data format.

12. The process of claim 3 further comprising converting the all-node-populated 3D matrix of well log data to a seismic data format.

13. The process of claim 11 wherein the seismic data format comprises SEG-Y or SEG P1.

14. The process of claim 11 further comprising interpreting the seismic data formatted 3D matrix.

15. The process of claim 12 further comprising interpreting the seismic data formatted 3D matrix.

16. The process of claim 14, wherein the interpretation is selected from petrophysical, log facies, structural and combinations thereof.

17. The process of claim 14, further comprising associating the interpretations with a well process at a specific well through the use of unique well identifiers.

18. The process of claim 14, wherein the well process comprises completion or production of oil and gas wells.

19. The process of claim 14, wherein the well process comprises the creation of pseudo wells to evaluate exploration opportunities.

20. The process of claim 15, wherein the well process comprises the creation of pseudo wells to evaluate exploration opportunities.