1. A method of determining the existence of and location of hydrocarbon and water fluid contacts by analyzing spatial changes in 3D seismic data comprising the steps of:
a. obtaining 3D dip data and azimuth data as at least one set of 3D volume data and deriving corresponding 3D reliability volumes or deriving 3D censor volumes which are representative of portions of the at least one set of 3D volume data within which 3D dip data and azimuth data can be reliably computed;
b. selecting a focused subvolume of interest within the at least one set of 3D volume data;
c. determining reliability locations within the focused subvolume of interest having non-null 3D dip data and non-null 3D azimuth data within the 3D reliability volumes or 3D censor volumes across the focused subvolume of interest forming a sequence of reliability locations;
d. computing an average for a plurality of vector dips around each reliability location in the sequence of the reliability locations forming at least one structural dip vector for each reliability location;
e. identifying a local subvolume of interest interior to the focused subvolume of interest for each reliability location wherein the local subvolume of interest contains 3D dip data and azimuth data as a set of vectors;
f. determining a flat spot direction vector for each structural dip vector at each reliability location;
g. forming a set of candidate flat spot dip vectors from at least one vector in the set of vectors within the local subvolume of interest and the at least one vector in the set of vectors are statistically consistent with the flat spot direction vector;
h. computing a significance measure for each vector within the set of candidate flat spot dip vectors;
i. forming and storing a 3D output subvolume comprising significance measures for all vectors in the set of candidate flat spot dip vectors;
j. repeating the method for all 3D volume data forming a 3D output volume.
2. The method of claim 1, wherein after determining a flat spot direction vector for each structural dip vector, a flat spot direction vector dip magnitude error quantity is calculated.
3. The method of claim 1, wherein after an average for a plurality of vector dips is computed, a standard deviation of X-Y-Z components for each structural dip vector for each reliability location is computed.
4. The method of claim 1, wherein the flat spot direction vector is computed from each structural dip vector using (1) petrophysical data at each reliability location, or (2) a user specified value for each structural dip vector for each reliability location.
5. The method of claim 1, wherein after a local subvolume of interest is identified, a set of local vectors within 1 standard deviation of the azimuth of the flat spot direction vector of at least one vector in the set of vectors is determined and dip magnitudes for each vector within the set of local vectors is computed.
6. The method of claim 1, further comprising the step of interpreting the 3D output volume to identify contiguous reliability location significance measures across a geologic structure for non-null values of the 3D output volume.
7. The method of claim 1, further comprising using user specified distances, positive and negative, along coordinate axes of focused subvolumes of interest to determine sizes of local subvolumes of interest around each reliability location.
8. The method of claim 1, further comprising using the 3D output volume to generate a plurality of contiguous significance locations which highlight water to hydrocarbons interfaces in subsurface geological structures.
9. The method of claim 8, further comprising the step of forming at least one group of contiguous significance locations and then determining a mean value for significance measures for each group and then determining standard deviations for significance measures for each group.
10. The method of claim 1, wherein the set of candidate flat spot dip vectors is formed using multivariate cluster analysis.
11. The method of claim 1, wherein the significance measure for each member of the set of candidate flat spot dip vectors is computed using multiple discriminate analysis or logistic regression.
12. Computer instructions on a computer readable media, comprising instructions to cause a processor to determine the existence of and location of hydrocarbon and water fluid contacts by analyzing spatial changes in 3D seismic data by performing the steps of:
a. obtaining 3D dip data and azimuth data as at least one set of 3D volume data and deriving corresponding 3D reliability volumes or deriving 3D censor volumes which are representative of portions of the at least one set of 3D volume data within which 3D dip data and azimuth data can be reliably computed;
b. selecting a focused subvolume of interest within the at least one set of 3D volume data;
c. determining reliability locations within the focused subvolume of interest having non-null 3D dip data and non-null 3D azimuth data within the 3D reliability volumes or 3D censor volumes across the focused subvolume of interest forming a sequence of reliability locations;
d. computing an average for a plurality of vector dips around each reliability location in the sequence of the reliability locations forming at least one structural dip vector for each reliability location;
e. identifying a local subvolume of interest interior to the focused subvolume of interest for each reliability location wherein the local subvolume of interest contains 3D dip data and azimuth data as a set of vectors;
f. determining a flat spot direction vector for each structural dip vector at each reliability location;
g. forming a set of candidate flat spot dip vectors from at least one vector in the set of vectors within the local subvolume of interest and the at least one vector in the set of vectors are statistically consistent with the flat spot direction vector;
h. computing a significance measure for each vector within the set of candidate flat spot dip vectors;
i. forming and storing a 3D output subvolume comprising significance measures for all vectors in the set of candidate flat spot dip vectors;
j. repeating the method for all 3D volume data forming a 3D output volume.
13. The computer instructions on computer readable media of claim 12, further comprising the instructions, wherein the 3D output subvolume further comprises additional null values and non-null values.
14. The computer instructions on computer readable media of claim 12, further comprising causing the processor to repeat the following steps for each reliability location within each focused subvolume of interest:
a. identifying a local subvolume of interest interior to the focused subvolume of interest for each reliability location wherein the local subvolume of interest contains 3D dip and azimuth data as a set of vectors;
b. forming a set of local vectors from a set of vectors that are within 1 standard deviation of the azimuth of the structural dip vector, or within a similarly user specified amount of deviation from the structural dip azimuth, and determining dip magnitudes for each vector within the set of local vectors;
c. forming a histogram of the dip magnitudes of the vectors within the subset of vectors; determining a flat spot direction vector for each structural dip vector at the reliability location, wherein the flat spot direction vector has a flat spot direction vector azimuth equaling a similarly user specified amount;
d. computing a flat spot direction vector dip magnitude from the structural dip magnitude using (1) petrophysical data at each reliability location, or (2) a user specified value of the structural dip magnitude for each reliability location;
e. determining a flat spot direction vector dip magnitude error quantity;
f. forming a set of candidate flat spot dip vectors when one or more local vectors are within the local subvolume of interest and the one or more local vectors are statistically consistent with the flat spot direction vector;
g. computing a significance measure for each vector within the set of candidate flat spot dip vectors; and
h. forming a 3D output subvolume comprising the significance measures for all vectors in the set of candidate flat spot dip vectors.
15. The computer instructions on computer readable media of claim 12, further comprising the instruction of causing the processor to interpret the 3D output volume to identify contiguous reliability location rates of change across a geologic structure for non-null values of the 3D output volume.
16. The computer instructions on computer readable media of claim 12, further comprising the instruction, wherein the processor utilizes user specified distances, positive and negative, along the coordinate axes to determine sizes of local subvolumes of interest around each reliability location.
17. The computer instructions on computer readable media of claim 12, further comprising instruction which cause the processor to use the 3D output volume to generate a plurality of contiguous significance locations which highlight water to hydrocarbons interfaces in subsurface geological structures.
18. The computer instructions on computer readable media of claim 12, further comprising an instruction to the processor to form at least one group of contiguous significance locations and then determining a mean value for significance measures for each group and then determining standard deviations for significance measures for each group.
19. The computer instructions on computer readable media of claim 12, wherein the instructions advise the processor to perform the steps of the method iteratively to all 3D seismic data on the earth.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
What is claimed is:
1. A magnetic sensing element comprising a multilayer film comprising an antiferromagnetic layer, a pinned magnetic layer, a nonmagnetic material layer, and a free magnetic layer,
wherein a current flows perpendicular to the planes of the individual layers of the multilayer film, and at least one of the pinned magnetic layer and the free magnetic layer comprises a half-metallic ferromagnetic alloy.
2. A magnetic sensing element according to claim 1, wherein the alloy is a Heusler alloy represented by the formula X2YZ, wherein X is an element selected from the group consisting of groups IIIA to IIB elements of the periodic table, Y is Mn, and Z is at least one element selected from the group consisting of Al, Si, Ga, Ge, In, Sn, Tl, Pb, and Sb.
3. A magnetic sensing element according to claim 2, wherein the Heusler alloy is Co2MnZ, wherein Z is at least one element selected from the group consisting of Al, Si, Ga, Ge, and Sn.
4. A magnetic sensing element according to claim 1, wherein the alloy is a Heusler alloy represented by the formula XYZ, wherein X is an element selected from the group consisting of groups IIIA to IIB elements of the periodic table, Y is Mn, and Z is at least one element selected from the group consisting of Al, Si, Ga, Ge, In, Sn, Tl, Pb, and Sb.
5. A magnetic sensing element according to claim 4, wherein the Heusler alloy is NiMnSb, PtMnSb, PdMnSb, or PtMnSn.
6. A magnetic sensing element according to claim 1, wherein the alloy is La0.7Sr0.3MnO3, CrO2, or F3O4.
7. A magnetic sensing element according to claim 1, wherein at least one of the pinned magnetic layer and the free magnetic layer has a laminated structure comprising at least first and second magnetic sublayers, and the first magnetic sublayer is in contact with the nonmagnetic material layer and comprises the half-metallic ferromagnetic alloy.
8. A magnetic sensing element according to claim 1, wherein at least one of the pinned magnetic layer and the free magnetic layer has a laminated structure including at least first and second magnetic sublayers, and the second magnetic sublayer is not in contact with the nonmagnetic material layer and comprises the half-metallic ferromagnetic alloy.
9. A magnetic sensing element according to claim 7, wherein the second magnetic sublayer comprises a magnetic material selected from the group consisting of CoFe alloys, CoFeNi alloys, NiFe alloys, and Co.
10. A magnetic sensing element according to claim 8, wherein the first magnetic sublayer comprises a magnetic material selected from the group consisting of CoFe alloys, CoFeNi alloys, NiFe alloys, and Co.
11. A magnetic sensing element according to claim 1, wherein at least one of the pinned magnetic layer and the free magnetic layer has a triple-layer structure including a central magnetic sublayer and two outer magnetic sublayers, and the central magnetic sublayer comprises the half-metallic ferromagnetic alloy.
12. A magnetic sensing element according to claim 11, wherein the outer magnetic sublayers comprise a magnetic material selected from the group consisting of CoFe alloys, CoFeNi alloys, NiFe alloys, and Co.
13. A magnetic sensing element according to claim 1, wherein at least one of the pinned magnetic layer and the free magnetic layer has a laminated ferrimagnetic structure including a first magnetic sublayer, a second magnetic sublayer, and an intermediate nonmagnetic sublayer, the first magnetic sublayer is in contact with the nonmagnetic material layer, and at least the first magnetic sublayer has a multilayer structure including a portion comprising the half-metallic ferromagnetic alloy or a single-layer structure comprising the half-metallic ferromagnetic alloy.