Abstract: A method is presented wherein inversion for formation anisotropic constants is achieved using borehole sonic data.

Abstract: Aspects provide for methods that successfully evaluates multiple compressional and shear arrival events received by a sonic logging tool to evaluate the presence of structures, such as shoulder beds, in downhole environments. In particular, the methods described herein enable automated determination of properties of laminated reservoir formations by, for example, enabling the automated determination of arrival times and slownesses of multiple compressional and shear arrival events received by a sonic logging tool.

Abstract: Embodiments provide a pressure meter testing apparatus and method that allows operations/engineers the ability to determine in-situ stiffness values of geological stratum.

Abstract: A method is presented wherein inversion for formation anisotropic constants is achieved using borehole sonic data.

Abstract: Embodiments provide a pressure meter testing apparatus and method that allows operations/engineers the ability to determine in-situ stiffness values of geological stratum.

Abstract: Anisotropic elastic properties and subsequently in situ stress properties for a rock formation surrounding a wellbore are computed from rock physics and geomechanical models. Mineralogy data measured from DRIFTS on cuttings from the wellbore and rock physics and geomechanical models that have been log-calibrated in another wellbore are used in the computation. The method includes: (1) Defining and calibrating rock physics and geomechanical models using data from the first wellbore; (2) using DRIFTS analysis to measure mineralogy data on rock cuttings obtained through drilling operation in the second wellbore; and (3) using previously calibrated models to estimate in situ stress properties, including a stress index and the minimum principal stress magnitude.

Abstract: Anisotropic elastic properties and subsequently in situ stress properties for a rock formation surrounding a wellbore are computed from rock physics and geomechanical models. Mineralogy data measured from DRIFTS on cuttings from the wellbore and rock physics and geomechanical models that have been log-calibrated in another wellbore are used in the computation. The method includes: (1) Defining and calibrating rock physics and geomechanical models using data from the first wellbore; (2) using DRIFTS analysis to measure mineralogy data on rock cuttings obtained through drilling operation in the second wellbore; and (3) using previously calibrated models to estimate in situ stress properties, including a stress index and the minimum principal stress magnitude.

Abstract: Methods and apparatus for estimating borehole mud slownesses are disclosed. An example method includes estimating a borehole drilling fluid slowness value based on a tube wave modulus value, a tube-wave slowness value, and a drilling fluid density value. The borehole is associated with an anisotropic elastic medium.

Abstract: Methods and systems for analyzing subterranean formations in-situ stress are disclosed. A method for extracting geological horizon on-demand from a 3D seismic data set, comprises receiving sonic log data; computing the anisotropic shear moduli C44, C55 and C66; determining in-situ stress type and selecting an in-situ stress expression corresponding to the in-situ stress type; computing stress regime factor Q of the formation interval; and computing and outputting the maximum stress ?H by using the stress regime factor Q, Vertical stress ?v and Minimum horizontal stress ?h.

Abstract: Methods and apparatus for estimating stress characteristics of formations. The method comprises: (a) acquiring sonic anisotropy data, image data or both associated with at least one borehole (b) employing sonic anisotropy data to estimate fast shear direction (FSA) to extract FSA observed data; (c) computing FSA from forward modeling, forward modeling utilizes a first deviatoric stress tensor to extract FSA predicted data; (d) computing FSA misfit from difference between FSA observed data and FSA predicted data to obtain computed FSA misfit relating to first deviatoric stress tensor; (e) if computed FSA misfit is equal to or less than a defined value, then store computed FSA misfit, otherwise repeat steps (d)-(h) using another deviatoric stress tensor so a different deviatoric stress tensor is used for each repeat; (f) selecting smallest stored computed misfit from group consisting of stored computed FSA misfit, at least one other stored computed misfit or combination thereof.

Abstract: Methods and apparatus for estimating stress characteristics of formations. The method comprises: (a) acquiring sonic anisotropy data, image data or both associated with at least one borehole (b) employing sonic anisotropy data to estimate fast shear direction (FSA) to extract FSA observed data; (c) computing FSA from forward modeling, forward modeling utilizes a first deviatoric stress tensor to extract FSA predicted data; (d) computing FSA misfit from difference between FSA observed data and FSA predicted data to obtain computed FSA misfit relating to first deviatoric stress tensor; (e) if computed FSA misfit is equal to or less than a defined value, then store computed FSA misfit, otherwise repeat steps (d)-(h) using another deviatoric stress tensor so a different deviatoric stress tensor is used for each repeat; (f) selecting smallest stored computed misfit from group consisting of stored computed FSA misfit, at least one other stored computed misfit or combination thereof.

Abstract: Methods and systems for analyzing subterranean formations in-situ stress are disclosed. A method for extracting geological horizon on-demand from a 3D seismic data set, comprises receiving sonic log data; computing the anisotropic shear moduli C44, C55 and C66; determining in-situ stress type and selecting an in-situ stress expression corresponding to the in-situ stress type; computing stress regime factor Q of the formation interval; and computing and outputting the maximum stress ?H by using the stress regime factor Q, Vertical stress ?v and Minimum horizontal stress ?h.