1-22. (canceled)
23. A computer-implemented method, comprising the following operations performed by at least one processor:
obtaining information associated with a social network;
identifying, based on the social networking information, a relationship between a first user and a second user of the social network;
based on the identified relationship, determining a portion of a contact list of the second user that is accessible to the first user; and
enabling the first user to access the determined portion of the contact list.
24. The method of claim 23, wherein:
the identified relationship comprises a direct relationship between the first and second users through zero intermediary users; and
the method further comprises:
identifying a category associated with the direct relationship; and
determining the accessible portion of the contact list of the second user based on the identified relationship and the identified category.
25. The method of claim 23, further comprising identifying a plurality of direct relationships through zero intermediary users.
26. The method of claim 25, further comprising:
identifying categories associated with the direct relationships based on the social networking information;
generating a composite category representative of the identified categories; and
determining the accessible portion of the contact list of the second user based on the composite category.
27. The method of claim 23, wherein the identified relationship comprises an indirect relationship between the first and second users through one or more intermediary users.
28. The method of claim 27, further comprising:
computing, for the indirect relationship, a degree of separation between the first and second users; and
determining the accessible portion of the contact list of the second user based on at least the degree of separation.
29. The method of claim 23, further comprising:
receiving, from the first user, a request to access the contact list of the second user, the request identifying the first user; and
identifying at least one characteristic of the first user based on the received request.
30. The method of claim 29, further comprising determining the accessible portion of the contact list of the second user based on the first user characteristic.
31. The method of claim 23, further comprising:
determining a type of access associated with the accessible portion of the contact list of the second user; and
enabling the first user to access the determined portion of the contact list of the second user in accordance with the access type.
32. The method of claim 32, further comprising:
determining, based on the social networking information, that no relationship exists between the first and second users; and
assigning a default type of access to the contact list of the second user, based on the determination that no relationship between the first and second users,
enabling the first user to access the determined portion of the contact list in accordance with the default access type.
33. An apparatus, comprising:
a storage device that stores a set of instructions; and
at least one processor coupled to the storage device and operative with the set of instructions to:
obtain information associated with a social network;
identify, based on the social networking information, a relationship between a first user and a second user of the social network;
based on the identified relationship, determine a portion of a contact list of the second user that is accessible to the first user; and
enable the first user to access the determined portion of the contact list.
34. The apparatus of claim 33, wherein:
the identified relationship comprises a direct relationship between the first and second users through zero intermediary users; and
the at least one processor is further configured to:
identify a category associated with the direct relationship; and
determine the accessible portion of the contact list of the second user based on the identified relationship and the identified category.
35. The apparatus of claim 33, wherein the at least one processor is further configured to identify a plurality of direct relationships through zero intermediary users.
36. The apparatus of claim 35, wherein the at least one processor is further operative to:
identify categories associated with the direct relationships based on the social networking information;
generate a composite category representative of the identified categories; and
determine the accessible portion of the contact list of the second user based on the composite category.
37. The apparatus of claim 33, wherein:
the identified relationship comprises an indirect relationship between the first and second users through one or more intermediary users; and
the at least one processor is further operative to:
compute, for the indirect relationship, a degree of separation between the first and second users; and
determine the accessible portion of the contact list of the second user based on at least the degree of separation.
38. The apparatus of claim 33, wherein the at least one processor is further operative to:
receive, from the first user, a request to access the contact list of the second user, the request identifying the first user; and
identify at least one characteristic of the first user based on the received request.
39. The apparatus of claim 38, wherein the at least one processor is further operative to determine the accessible portion of the contact list of the second user based on the first user characteristic.
40. The apparatus of claim 33, wherein the at least one processor is further operative to:
determine a type of access associated with the accessible portion of the contact list of the second user; and
enable the first user to access the determined portion of the contact list in accordance with the access type.
41. The apparatus of claim 40, wherein the at least one processor is further operative to:
determine, based on the social networking information, that no relationship exists between the first and second users; and
assign a default type of access to the contact list of the second user, based on the determination that no relationship exists between the first and second users,
enable the first user to access the determined portion of the contact list in accordance with the default access type.
42. A tangible, non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform a method comprising:
obtaining information associated with a social network;
identifying, based on the social networking information, a relationship between a first user and a second user of the social network;
based on the identified relationship, determining a portion of a contact list of the second user that is accessible to the first user; and
enabling the first user to access the determined portion of the contact list.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method, comprising:
gathering data regarding a plurality of completed wellbores;
gathering data regarding an uncompleted wellbore;
utilizing the gathered data regarding the plurality of completed wellbores in the field to define a plurality of predictive models, each of the plurality of predictive models providing an estimate of wellbore production based on the gathered data regarding the plurality of completed wellbores;
identifying a best predictive model from the plurality of predictive models;
applying the gathered data regarding the uncompleted wellbore and a plurality of available wellbore completion parameters to the best predictive model to identify a set of wellbore completion parameters from the plurality of available wellbore completion parameters that optimizes estimated wellbore production based on the best predictive model; and
completing the uncompleted wellbore based on the set of wellbore completion parameters identified using the best predictive model.
2. The method of claim 1, wherein the gathered data regarding the plurality of completed wellbores comprises mud log data.
3. The method of claim 2, wherein the gathered data regarding the uncompleted wellbore comprises mud log data.
4. The method of claim 1, wherein utilizing the gathered data regarding the plurality of completed wellbores to define the plurality of predictive models comprises applying the gathered data regarding the plurality of completed wellbores to an artificial neural network.
5. The method of claim 4, wherein applying the gathered data regarding the plurality of completed wellbores to the artificial neural network includes applying the data gathered for a first set of completed wellbores from the plurality of completed wellbores to the artificial neural network, wherein the first set of the plurality of completed wellbores is less than all of the plurality of completed wellbores.
6. The method of claim 5, wherein identifying the best predictive model from the plurality of predictive models comprises applying the data gathered for a second set of completed wellbores from the plurality of completed wellbores to the plurality of predictive models, the second set of completed wellbores being different from the first set of completed wellbores.
7. The method of claim 6, wherein identifying the best predictive model from the plurality of predictive models further comprises evaluating each of the plurality of predictive models relative to one or more evaluation factors.
8. The method of claim 7, wherein the one or more evaluation factors include factors selected from the group of factors consisting of number of data input parameters and whether the predictive model utilizes hydrocarbon ratios.
9. The method of claim 8, wherein predictive models with a lower number of data input parameters are favored.
10. The method of claim 8, wherein predictive models that utilize at least one hydrocarbon ratio are favored.
11. The method of claim 8, wherein the one or more evaluation factors further includes parameter sensitivity.
12. The method of claim 1, wherein the set of wellbore completion parameters that optimizes estimated wellbore production includes a total number of hydraulic fractures.
13. The method of claim 12, wherein the set of wellbore completion parameters that optimizes estimated wellbore production further includes hydraulic fracture spacings along the uncompleted well.
14. The method of claim 13, wherein the hydraulic fracture spacings vary along the uncompleted well.
15. The method of claim 1, wherein the set of wellbore completion parameters that optimizes estimated wellbore production further includes hydraulic fracture volumes.
16. The method of claim 1, wherein the set of wellbore completion parameters that optimizes estimated wellbore production further includes hydraulic fracture fluid type.
17. The method of claim 1, wherein the set of wellbore completion parameters that optimizes estimated wellbore production further includes hydraulic fracture proppant type.
18. The method of claim 1, wherein the set of wellbore completion parameters that optimizes estimated wellbore production further includes hydraulic fracture staging type.
19. The method of claim 1, wherein utilizing the gathered data regarding the plurality of completed wellbores in the field to define the plurality of predictive models includes identifying correlating factors.
20. The method of claim 19, wherein identifying correlating factors includes applying multivariate analysis.
21. The method of claim 19, wherein identifying correlating factors includes applying cluster analysis.
22. The method of claim 19, wherein identifying correlating factors includes generating one or more visual representations of the gathered data selected from the group of visual representations consisting of a scatter plot, a bi-plot, a dendrogram, and a self-organizing map.
23. The method of claim 1, wherein the uncompleted wellbore and the plurality of completed wellbores are within a single field.
24. The method of claim 1, wherein the uncompleted wellbore and the plurality of completed wellbores are from a plurality of fields.
25. The method of claim 24, wherein at least one of the plurality of completed wellbores is from a first field and the uncompleted wellbore is from a second field, the second field being different than the first field.
26. A computer-implemented system for optimizing wellbore completion, the system including a non-transitory, computer readable medium having a plurality of instructions stored thereon for executing the following steps:
receiving data regarding a plurality of completed wellbores in a field;
receiving data regarding an uncompleted wellbore in the field;
utilizing the gathered data regarding the plurality of completed wellbores in the field to define a plurality of predictive models, each of the plurality of predictive models providing an estimate of wellbore production based on the gathered data regarding the plurality of completed wellbores;
identifying a best predictive model from the plurality of predictive models;
applying the gathered data regarding the uncompleted wellbore and a plurality of available wellbore completion parameters to the best predictive model to identify a set of wellbore completion parameters from the plurality of available wellbore completion parameters that optimizes estimated wellbore production based on the best predictive model; and
outputting the set of wellbore completion parameters identified using the best predictive model in human-intelligible form.