Exxonmobil Upstream Research Company

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Anoop A Mullur

Rebecca L Saltzer

Charlie Jing

Christopher J DiCaprio

Jan Schmedes

Garrett M Leahy

Pavel Dimitrov

Dennis E Willen

Jerome R Krebs

Partha Sarathi Routh

Thomas A Dickens

Sunwoong Lee

Vikas Goel

Valeriy V Brytik

Young Ho Cha

Hong Zhao

Nathan Downey

Federico D Carvallo

Michael B Townsley

Praveen Nakshatrala

Cassandra M McZeal

Eva-Maria Rumpfhuber

Jim J Carazzone

Aleksandar Bobrek

Christopher S Beard

Arrian M Brantley

Christopher Dicaprio

Cassandra Mczeal

Federico Carvallo

Rebecca Saltzer

A method, including: obtaining, with a computer, an initial geophysical model; modeling, with a computer, a forward wavefield based on the initial geophysical model with wave equations including a second order z-derivative in a rotated coordinate system that accounts for a tilted transverse isotropic (TTI) medium; modeling, with a computer, an adjoint wavefield with adjoint wave equations including a second order z-derivative in a rotated coordinate system that accounts for a tilted transverse isotropic (TTI) medium, wherein the wave equations and the adjoint wave equations include relaxation terms accounting for anelasticity of earth in an update of a primary variable and an evolution relationship for the relaxation terms; and obtaining, with a computer, a gradient of a cost function based on a combination of a model of the forward wavefield and a model of the adjoint wavefield.

Visco-pseudo-elastic TTI FWI/RTM formulation and implementation

System and method for scalable and reliable scheduling of iterative seismic full wavefield inversion algorithms with alternating parallel and serial stages of computation on massively parallel computing systems. The workers are independent, initiating actions and unaware of each other, and given limited information. This enables application of optimal scheduling, load-balancing, and reliability techniques specific to seismic inversion problems. The central dispatcher specifies the structure of the inversion, including task dependency, and keeps track of progress of work. Management tools enable the user to make performance and reliability improvements during the execution of the seismic inversion.

Scalable scheduling of parallel iterative seismic jobs

Method for estimating porosity and water saturation or other geological parameters of a subsurface region when the lithology of the region is unknown, requiring only geophysical data from remote surveys. The geophysical data are inverted (-) treating lithology as a third, and discrete, unknown model parameter () to be solved for in the inversion. A technique for solving mixed integer non-linear programs may be used. Suitable rock physics relationships () are used to relate the desired geological parameters to the geophysical model parameters required for simulating the geophysical data in the inversion process.

Inverting geophysical data for geological parameters or lithology

Method for performing simultaneous encoded-source inversion of geophysical data to estimate parameters of a physical property model (), especially adapted for surveys without fixed-receiver acquisition geometry, such as marine seismic surveys with moving source and receivers. The encoding functions () used on the sources to generate one or more simultaneous encoded-source gathers of data (), as well as to simulate the same (), are orthogonal or pseudo-orthogonal with respect to cross-correlation. In addition, receivers are also encoded, with the receiver encoding being designed to make a given receiver less sensitive to sources to which it was not listening during the survey (). The encoding functions may be temporal bandpass filters differing one from another by central frequency, phase, or both. Efficiency of the method may be further improved by grouping several sources into a super-source, grouping the corresponding gathers into a super-gather, and then applying the above encoding strategy.

Orthogonal source and receiver encoding

Method for estimating geological properties in a subsurface region using multiple types of geophysical data (). An initial physical properties modelis constructed. Some parameters in the model are frozen () and optionally portions of the model wave number and spatial domains () and the data frequency and data time domains (), are also frozen. Then, a joint inversion () of the multiple data types is performed to calculate an update to the model only for the portions that are not frozen. The converged model () for this inversion is used as a new starting model, and the process is repeated (), possibly several times, unfreezing more parameters and data each time until the desired spatial and parameter resolution () has been achieved.

Domain freezing in joint inversion

Method for adaptive weighting of geophysical data types in iterative joint inversion to speed convergence and aid escape from local minima of the penalty (objective) function. Two or more geophysical data sets () representing a region of interest are obtained, and are jointly inverted to infer models of the physical properties that affect the particular types of data used. The misfit for each data type is a weighted tem in the penalty function (). The invention involves changing the weights () as the iteration cycles progress when the iteration convergence criteria are satisfied (), to see if they remain satisfied () with the modified penalty function.

Adaptive weighting of geophysical data types in joint inversion

Method for joint inversion of geophysical data to obtain 3-D models of geological parameters for subsurface regions of unknown lithology. Two or more data sets of independent geophysical data types are obtained, e.g. seismic and electromagnetic. Then they are jointly inverted, using structural coupling, to infer geophysical parameter volumes, e.g. acoustic velocity and resistivity. Regions of common lithology are next identified based on similar combinations of geophysical parameters. Then a joint inversion of the multiple data types is performed in which rock physics relations vary spatially in accordance with the now-known lithology, and 3-D models of geological properties such as shale content and fracture density are inferred. The computational grid for the last inversion may be defined by the lithology regions, resulting in average geological properties over such regions, which may then be perturbed to determine uncertainty in lithologic boundaries.

Joint inversion with unknown lithology

Method for reducing a 3D joint inversion of at least two different types of geophysical data acquired by 3-D surveys to an equivalent set of 1D inversions. First, a 3D inversion is performed on each data type separately to the yield a 3-D model of a physical property corresponding to the data type. Next, a 1D model of the physical property is extracted at selected (x,y) locations. A 1D simulator and the 1D model of the physical property is then used at each of the selected locations to create a synthetic 1D data set at each location. Finally, the 1D synthetic data sets for each different type of geophysical data are jointly inverted at each of the selected locations, yielding improved values of the physical properties. Because the joint inversion is a 1D inversion, the method is computationally advantageous, while recognizing the impact of 3-D effects.

Reducing the dimensionality of the joint inversion problem

Method for using seismic data from earthquakes to address the low frequency lacuna problem in traditional hydrocarbon exploration methods. Seismometers with frequency response down to about 1 Hz are placed over a target subsurface region in an array with spacing suitable for hydrocarbon exploration (). Data are collected over a long (weeks or months) time period (). Segments of the data () are identified with known events from earthquake catalogs (). Those data segments are analyzed using techniques such as traveltime delay measurements () or receiver function calculations () and then are combined with one or more other types of geophysical data acquired from the target region, using joint inversion (-) in some embodiments of the method, to infer physical features of the subsurface indicative of hydrocarbon potential or lack thereof ().

Hydrocarbon detection with passive seismic data

Systems and methods which implement surrogate (e.g., approximation) models to systematically reduce the parameter space in an optimization problem are shown. In certain embodiments, rigorous (e.g., higher fidelity) models are implemented with respect to the reduced parameter space provided by use of surrogate models to efficiently and more rapidly arrive at an optimized solution. Accordingly, certain embodiments build surrogate models of an actual simulation, and systematically reduce the number of design parameters used in the actual simulation to solve optimization problems using the actual simulation. A multi-stage method that facilitates optimization of decisions related to development planning and reservoir management may be provided. Iterative processing may be implemented with respect to a multi-stage optimization method. There may be uncertainty in various parameters, such as in reservoir parameters, which is taken into account according to certain embodiments.

Systems and methods for reservoir development and management optimization

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Houston, TX, United States of America

Anoop A Mullur