Exxonmobil Upstream Research Company

Dmitriy A Pavlov

Leonard J Srnka

James J Carazzone

Dennis E Willen

Charlie Jing

Leslie A Wahrmund

Olivier M Burtz

Scott C Hornbostel

Richard T Houck

Kenneth E Green

There is provided a system and method for creating a physical property model representative of a physical property of a region. An exemplary method comprises transforming information from a model domain that represents the physical property model into simulated data in a data domain, the data domain comprising simulated data and measured data representative of a plurality of observations of the region. The exemplary method also comprises determining an areal misfit between the simulated data and the measured data representative of the plurality of observations of the region. The exemplary method additionally comprises performing an evaluation of the areal misfit based on known criteria. The exemplary method comprises adjusting data in the data domain or information in the model domain corresponding to a region in the model domain based on the evaluation of the areal misfit.

System and method for providing a physical property model

Method for rapid inversion of data from a controlled-source electromagnetic survey of a subterranean region. Selected () common-receiver or common-source gathers of the data are reformed into composite gathers () by summing their data. Each composite gather is forward modeled (in the inversion process) with multiple active source locations (). Computer time is reduced in proportion to the ratio of the total number of composite gathers to the total number of original common-receiver or common-source gathers. The data may be phase encoded to prevent data cancellation. Methods for mitigating loss of far offset information by data overlap in the summing process are disclosed.

Rapid inversion of electromagnetic reconnaissance survey data

Method for determining receiver orientation angles in a controlled source electromagnetic survey, by analyzing the survey data. For a given survey receiver, two data subsets are selected. (). The two subsets may be from two offset ranges that are geometrically symmetrical relative to the receiver location. Alternatively, the second subset may be a computer simulation of actual survey data. In either instance, an orientation is assumed for the receiver (), and that orientation is used to compare component data from the two subsets that can be expected to match if the assumed orientation angle(s) is (are) correct (). The mismatch is ascertained, and the assumed orientation is adjusted () and the process is repeated.

Method for determining orientation of electromagnetic receivers

Method for determining time-dependent changes [] in the earth vertical and horizontal electrical resistivity and fluid saturations from offshore electromagnetic survey measurements. The method requires both online and offline data, which should include at least one electromagnetic field component sensitive at least predominantly to vertical resistivity and another component sensitive at least predominately to horizontal resistivity []. Using a horizontal electric dipole source, online Ez and offline Hz measurements are preferred. For a horizontal magnetic dipole source, online Hand offline Edata are preferred. Magnetotelluric data may be substituted for controlled source data sensitive at least predominantly to horizontal resistivity. Maxwell's equations are solved by forward modeling [or by inversion [, using resistivity models of the subsurface that are either isotropic contrast, and [or anisotropic [. Fluid saturation is determined from the vertical and horizontal resistivities using empirical relations or rock physics models [

Time lapse analysis with electromagnetic data

Method for generating a three-dimensional resistivity data volume for a subsurface region from an initial resistivity model and measured electromagnetic field data from an electromagnetic survey of the region, where the initial resistivity model is preferably obtained by performing multiple ID inversions of the measured data []. The resulting resistivity depth profiles are then registered at proper 3D positions []. The 3D electromagnetic response is simulated [] assuming the resistivity structure is given by the initial resistivity model. The measured electromagnetic field data volume is scaled by the simulated results [] and the ratios are registered at proper 3D positions [] producing a ratio data volume []. A 3D resistivity volume is then generated by multiplying the initial resistivity volume by the ratio data volume (or some function of it), location-by location []. A related method emphasizes deeper resistive anomalies over masking effects of shallow anomalies.

Method for obtaining resistivity from controlled source electromagnetic data

Method for conducting an efficient and interpretable controlled-source electromagnetic reconnaissance survey for buried hydrocarbons. While a part of the survey area is being set up for measurement and data are being acquired, data from a nearby part of the survey area, surveyed just previously, are being rapidly processed and analyzed. If the analysis shows resistive anomalies of interest in a portion of a survey area, a fine-grid survey is quickly designed for that portion, and that survey is conducted next before moving source and receivers to a more distant part of the survey area.

Method for controlled source electromagnetic reconnaissance surveying

The method for correcting the phase of measured electric signals or magnetic signals of field data from a controlled source electromagnetic survey (CSES) by comparing the measured field data corresponding to a selected frequency to the simulated data for various signal source receiver offsets () and correcting the phases of the actual data based on the phase difference for a selected range of small signal offsets () based on a go-electric model.

Method for phase and amplitude correction in controlled source electromagnetic survey data

Method for determining an expected value for a proposed reconnaissance electromagnetic (or any other type of geophysical) survey using a user-controlled source. The method requires only available geologic and economic information about the survey region. A series of calibration surveys are simulated with an assortment of resistive targets consistent with the known information. The calibration surveys are used to train pattern recognition software to assess the economic potential from anomalous resistivity maps. The calibrated classifier is then used on further simulated surveys of the area to generate probabilities that can be used in Value of Information theory to predict an expected value of a survey of the same design as the simulated surveys. The calibrated classifier technique can also be used to interpret actual CSEM survey results for economic potential.

Design of reconnaissance surveys using controlled source electromagnetic fields via probabilistic neural network

Method for conducting an efficient and interpretable controlled-source electromagnetic reconnaissance survey for buried hydrocarbons. While a part of the survey area is being set up for measurement and data are being acquired, data from a nearby part of the survey area, surveyed just previously, are being rapidly processed and analyzed (). If the analysis shows resistive anomalies of interest in a portion of a survey area, a fine-grid survey is quickly designed for that portion, and that survey is conducted next before moving source and receivers to a more distant part of the survey area.

Method for removing effects of shallow resistivity structures in electromagnetic survey data to produce a low frequency resistivity anomaly map, or alternatively imaging resistivity structures at their correct depth levels. The method involves solving Maxwell's electromagnetic field equations by either forward modeling or inversion, and requires at least two survey data sets, one taken at the source frequency selected to penetrate to a target depth, the other a higher frequency able to penetrate only shallow depths.

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The Woodlands, TX, United States of America

Dmitriy A Pavlov