A method includes determining a present-day thickness of a lithosphere. The method also includes determining whether the determined present-day thickness of the lithosphere substantially matches an interpreted present-day thickness of the lithosphere. The method also includes generating or updating a temperature history model in response to determining that the determined present-day thickness of the lithosphere substantially matches the interpreted present-day thickness of the lithosphere.

Methods and systems for calibrating a subsidence map are disclosed. The method includes selecting a stratigraphic model that represents a geological formation and defining the subsidence map with a first set of variable values. The method further includes obtaining target outputs measured from the geological formation. The method still further includes determining first model outputs from the stratigraphic model by inputting the subsidence map with the first set of variable values into the stratigraphic model and determining a first residual between the target outputs and the first model outputs using an objective function.

A system (100) for monitoring a field (20) under a body of water, wherein the system (100) comprises a reference station (112) and a plurality of permanent seafloor sensors (120, 121). Each permanent seafloor sensor (120, 121) is fixed relative to a seafloor (2) on or at the field (20). The seafloor sensor (120, 121) further has a nearby survey station (111) sufficiently distant to ensure that a movable sensor (122) visiting the nearby survey station (111) does not disturb measurements from the permanent seafloor sensor (120). The distance is sufficiently close to ensure that the offset (Δp, Δg) from a value provided by the permanent seafloor sensor (120) is constant or can be modelled, e.g. to account for changes in the pressure/depth relation due to changes in water density. Each seafloor sensor is associated with a unique drift function d(t) at least comprising a drift rate (a). Thus, each permanent seafloor (120, 121) sensor provide an output that is corrected for drift at any time between calibration surveys. The system may be used for permanent monitoring of a seafloor.

A system (100) for monitoring a field (20) under a body of water, wherein the system (100) comprises a reference station (112) and a plurality of permanent seafloor sensors (120, 121). Each permanent seafloor sensor (120, 121) is fixed relative to a seafloor (2) on or at the field (20). The seafloor sensor (120, 121) further has a nearby survey station (111) sufficiently distant to ensure that a movable sensor (122) visiting the nearby survey station (111) does not disturb measurements from the permanent seafloor sensor (120). The distance is sufficiently close to ensure that the offset (p, g) from a value provided by the permanent seafloor sensor (120) is constant or can be modelled, e.g. to account for changes in the pressure/depth relation due to changes in water density. Each seafloor sensor is associated with a unique drift function d(t) at least comprising a drift rate (a). Thus, each permanent seafloor (120, 121) sensor provide an output that is corrected for drift at any time between calibration surveys. The system may be used for permanent monitoring of a seafloor.

The present disclosure includes a method for suppressing 4D noise. The method includes calculating a first similarity map based on the similarity of one of one or more first 3D images and a second 3D image. The first and second 3D images are derived from first and second surveys, respectively. The method also includes calculating a second similarity map based on the similarity of one of the one or more first 3D images and a third 3D image, which is derived from the second survey. The method also includes calculating a third similarity map based on the similarity of first and second 4D images, which are based on differences between the 3D images. The method also includes generating a composite 4D image based at least on the first, second, and third similarity maps. The present disclosure may also include associated systems and apparatus.

System and methods are disclosed. The method includes obtaining an observed stratigraphic thickness map, initial bathymetry map, and initial subsidence sequence for a model of the geological region of interest, where the model comprises a plurality of cells each representing a portion of the geological region. The methods further includes simulating, using a forward stratigraphic modeler, a predicted stratigraphic thickness map for each cell based on the initial subsidence sequence, then iteratively, forming an objective function for each cell based, at least in part, on the observed stratigraphic thickness map and the predicted stratigraphic thickness map, determining if the objective function for each cell satisfies a stopping criterion, and updating the subsidence sequence for cells not satisfying the criterion. The methods still further include, assigning the subsidence sequence satisfying the stopping criterion to be a validated subsidence sequence and the predicted stratigraphic map to be a calibrated stratigraphic map.

A time-lapse seismic wavefield monitoring system for a formation includes at least one seismic wavefield source and at least one seismic wavefield sensor to collect seismic wavefield survey data corresponding to the formation in response to an emission from the at least one seismic wavefield source. The seismic wavefield survey data includes first seismic wavefield data collected at a first time and second seismic wavefield data collected at a second time. The time-lapse seismic wavefield monitoring system also includes a processing unit in communication with the at least one seismic wavefield sensor. The processing unit determines time-lapsed seismic wavefield data based on the first seismic wavefield data and the second seismic wavefield data, and performs an analysis of the time-lapsed seismic wavefield data to determine an attribute change in an earth model.

A method for measuring subsidence and/or uprise on a field, comprises the steps of: deploying at least one cable on a solid surface; collecting inline tilt data from numerous tilt sensors deployed along each cable (100); and performing a statistical analysis on the tilt data to determine changes in curvature on the solid surface. Preferably, the statistical method involves computing a cumulative inline and/or cross-line tilt, whereby random errors cancel and systematic changes add. In addition, regression and/or interpolation may provide a quantitative estimate of curvature etc.