Abstract Disclosed is a method for characterising the evolution of a subsurface volume over time. The method comprises providing first and second surveys of the subsurface volume. Each survey comprises seismic data acquired by transmitting seismic signals into the subsurface volume and subsequently detecting some or all of the seismic signals after reflection within the subsurface. The first seismic data of the first survey corresponds to a first time and the second seismic data of the second survey corresponds to a second time. At least some of the first seismic data and the second seismic data is obtained with a non-zero offset. An inversion is performed to obtain estimates of changes having occurred between the first time and the second time in terms of at least one model parameter; wherein for the inversion: the first seismic data and the second seismic data is not processed to be equivalent to zero-offset data prior to the inversion; and it is assumed that the path taken by each received seismic signal between its transmission and reception is the same for the first survey and the second survey

Methods and apparatus are described for performing a 4D monitor marine seismic survey that repeats a previous survey. A number of sources may be used during the 4D monitor survey that differs from a number of sources that were used during the previous survey. Shot points from the previous survey are repeated by the 4D monitor survey, and additional shot points may be produced during the 4D monitor survey that were not produced during the previous survey. Embodiments enable efficiency and data quality improvements to be captured during 4D survey processes, while preserving repeatability.

A method for training a backpropagation-enabled regression process is used for predicting values of an attribute of subsurface data. A multi-dimensional seismic data set with an input dimension of at least two is inputted into a backpropagation-enabled process. A predicted value of the attribute has a prediction dimension of at least 1 and is at least 1 dimension less than the input dimension.

A method and system for forming a seismic image of a subterranean region are disclosed. The method includes determining an initial plan for a seismic survey with a value for each member of a set of acquisition parameters and acquiring a first seismic dataset from a first portion of the seismic survey based on the initial plan. The method further includes transmitting the first seismic dataset to a seismic processor, determining a first seismic image from the first seismic dataset by performing expedited seismic processing and determining a first updated plan for the seismic survey based on the first seismic image and acquiring a second seismic dataset from a second portion of the seismic survey based on the first updated plan. The method still further includes transmitting the second seismic dataset to the seismic processor and determining the seismic based on the first seismic dataset and the second seismic dataset.

A computer implemented method for analyzing a reservoir grid modeling a reservoir geological formation is provided in which the reservoir grid corresponds to a 3D grid of cells associated to respective values of at least one geological property. The method includes obtaining a 4D seismic image of the reservoir geological formation. A skeleton of the 4D seismic image is calculated, and the skeleton extends between at least one origin and a plurality of extremities. Each point of the skeleton is associated to a value of the at least one geological property of the reservoir grid. Flow time values are calculated for a fluid flowing from the origin to the extremities along the skeleton, based on the at least one geological property values associated to the points of the skeleton. The reservoir grid is calculated based on the flow time values.

A method of exploring for hydrocarbons in a region, including the steps of obtaining seismic data for the region corresponding to two or more different times and analyzing the seismic data corresponding to the two or more different times to determine whether there are any changes in the seismic data.

A DAS VSP technique is used to determine the induced fracture height and fracture density of an induced fracture region. The DAS VSP technique obtains pre-hydraulic fracturing DAS VSP survey time-lapse data to establish a baseline reference for the direct acoustic wave travel time. The DAS VSP technique obtains one or more time-lapse data corresponding to the subsequent monitor surveys conducted after each hydraulic fracturing stage along the well. Forward modeling is used to determine a theoretical acoustic wave travel time difference. The forward modeling uses seismic anisotropy to describe the behavior of seismic waves traveling through the induced fracture regions. An inversion scheme is then used to invert for the induced fracture height and the fracture density using the forward modeling. The two extracted induced fracture characteristics may then be used to determine optimal hydraulic fracturing parameters.

The present invention belongs to the field of treatment for data identification and recording carriers, and specifically relates to a method and system for analyzing filling for a karst reservoir based on spectrum decomposition and machine learning, which aims to solve the problems that by adopting the existing petroleum exploration technology, the reservoir with fast lateral change cannot be predicted, and the development characteristics of a carbonate cave type reservoir in a large-scale complex basin cannot be identified. The method comprises: acquiring data of standardized logging curves; obtaining a high-precision 3D seismic amplitude data body by mixed-phase wavelet estimation and maximum posteriori deconvolution and enhancing diffusion filtering. According to the method and the system, the effect of identifying the development characteristics of the carbonate karst cave type reservoir in the large-scale complex basin can be achieved, and the characterization precision is improved.

System and methods for predicting time-dependent rock properties are provided. Seismic data for a subsurface formation is acquired over a plurality of time intervals. A value of at least one rock property of the subsurface formation is calculated for each of the plurality of time intervals, based on the corresponding seismic data acquired for that time interval. At least one of a trend or a spatio-temporal relationship in the seismic data is determined based on the value of the at least one rock property calculated for each time interval. A value of the at least one rock property is estimated for a future time interval, based on the determination. The estimated value of the at least one rock property is used to select a location for a wellbore to be drilled within the subsurface formation. The wellbore is then drilled at the selected location.

Techniques are disclosed for reducing noise when computing time-lapse differences between two or more geophysical surveys performed over the same region. In some computer-implemented embodiments, a time-lapse difference is determined between first and second data representing the first and second surveys, respectively. Based on geometry information corresponding to the second survey, first estimated data is generated representing how the first data would have looked if the second survey geometry had been used during the first survey. A noise model is generated based on differences between the first data and the first estimated data. The time-lapse difference is then adjusted using the noise model, thereby reducing noise in the time-lapse difference caused by differences between the geometries of the first and second surveys.