Abstract: Methods and systems are provided for characterizing connate water salinity and resistivity of a subsurface formation. Well log data including resistivity and spontaneous potential (SP) log data are measured by at least one downhole tool disposed within a borehole. The resistivity and SP log data are inverted to determine a resistivity model and an SP model, which are used to determine connate water resistivity. The connate water resistivity is used to determine connate water salinity. The connate water salinity derived from the inversion of resistivity log data and SP log data (or derived from a trained ML system supplied with such log data) can be used as a baseline measure of connate water salinity, and this baseline measure can be evaluated together with the connate water salinity estimates derived from pulsed neutron tool measurements over time-lapsed periods of production to monitor variation in connate water salinity due to production.

Abstract: Processes for characterizing reservoir formations and directing downhole operations based on the characterized reservoir formations. In some embodiments, the process can include combining at least two downhole logs into input data. An interpretation method can be used to convert the input data into interpretative data. Elemental analysis can be used to convert the interpretative data into at least one formation model. Formation properties can be acquired from the at least one formation model. A reservoir quality classification can be created from the formation properties. The process can also include directing downhole operations using the reservoir quality classification to select a preferred downhole operation location.

Abstract: Methods and systems are provided for characterizing connate water salinity and resistivity of a subsurface formation. Well log data including resistivity and spontaneous potential (SP) log data are measured by at least one downhole tool disposed within a borehole. The resistivity and SP log data are inverted to determine a resistivity model and an SP model, which are used to determine connate water resistivity. The connate water resistivity is used to determine connate water salinity. The connate water salinity derived from the inversion of resistivity log data and SP log data (or derived from a trained ML system supplied with such log data) can be used as a baseline measure of connate water salinity, and this baseline measure can be evaluated together with the connate water salinity estimates derived from pulsed neutron tool measurements over time-lapsed periods of production to monitor variation in connate water salinity due to production.

Abstract: Methods and systems are provided that perform sonic measurements in a high-angle wellbore or horizontal wellbore or vertical wellbore penetrating highly dipped formation layers where the formation layers can have a high degree of dip relative to the wellbore. Sonic data can be generated from the sonic measurements and processed using multiple arrival event processing to determine formation porosity, elastic rock properties and geometric information for a tool layer and nearby shoulder bed. Such information can be integrated into a 2D or 3D layered model of the formation. The elastic rock properties of the tool layer and shoulder bed derived from the multiple arrival event processing can provide more representative elastic property values, which can account for heterogeneity along the wellbore.