Resolution attributes for geophysical inversion models: Depth of investigation and novel measures

2021 ◽  
Author(s):  
Niels B. Christensen
2021 ◽  
Author(s):  
Alexis Neven ◽  
Pradip Kumar Maurya ◽  
Anders Vest Christiansen ◽  
Philippe Renard

Abstract. Quaternary deposits are complex and heterogeneous. They contain some of the most abundant and extensively used aquifers. In order to improve the knowledge of the spatial heterogeneity of such deposits, we acquired a large (more than 1400 hectares) and dense (20 m spacing) Time Domain ElectroMagnetic (TDEM) dataset in the upper Aare Valley, Switzerland. TDEM is a fast and reliable method to measure the magnetic field directly related to the resistivity of the underground. In this paper, we present the inverted resistivity models derived from this acquisition, and all the necessary data in order to perform different inversions on the processed data (https://doi.org/10.5281/ZENODO.4269887 (Neven et al., 2020)). The depth of investigation ranges between 40 to 120 m depth, with an average data residual contained in the standard deviation of the data. These data can be used for many different purposes: from sedimentological interpretation of quaternary environments in alpine environments, geological and hydrogeological modeling, to benchmarking geophysical inversion techniques.


2021 ◽  
Vol 13 (6) ◽  
pp. 2743-2752
Author(s):  
Alexis Neven ◽  
Pradip Kumar Maurya ◽  
Anders Vest Christiansen ◽  
Philippe Renard

Abstract. Quaternary deposits are complex and heterogeneous. They contain some of the most abundant and extensively used aquifers. In order to improve the knowledge of the spatial heterogeneity of such deposits, we acquired a large (1500 ha) and dense (20 m spacing) time domain electromagnetic (TDEM) data set in the upper Aare Valley, Switzerland (available at https://doi.org/10.5281/zenodo.4269887; Neven et al., 2020). TDEM is a fast and reliable method to measure the magnetic field directly related to the resistivity of the underground. In this paper, we present the inverted resistivity models derived from this acquisition. The depth of investigation ranges between 40 and 120 m, with an average data residual contained in the standard deviation of the data. These data can be used for many different purposes: from sedimentological interpretation of quaternary environments in alpine environments, geological and hydrogeological modeling, to benchmarking geophysical inversion techniques.


Author(s):  
Matthew Blyth ◽  
◽  
Naoki Sakiyama ◽  
Hiroshi Hori ◽  
Hiroaki Yamamoto ◽  
...  

A new logging-while-drilling (LWD) acoustic tool has been developed with novel ultrasonic pitch-catch and pulse-echo technologies. The tool enables both high-resolution slowness and reflectivity images, which cannot be addressed with conventional acoustic logging. Measuring formation elastic-wave properties in complex, finely layered formations is routinely attempted with sonic tools that measure slowness over a receiver array with a length of 2 ft or more depending upon the tool design. These apertures lead to processing results with similar vertical resolutions, obscuring the true slowness of any layering occurring at a finer scale. If any of these layers present significantly different elastic-wave properties than the surrounding rock, then they can play a major role in both wellbore stability and hydraulic fracturing but can be absent from geomechanical models built on routine sonic measurements. Conventional sonic tools operate in the 0.1- to 20-kHz frequency range and can deliver slowness information with approximately 1 ft or more depth of investigation. This is sufficient to investigate the far-field slowness values but makes it very challenging to evaluate the near-wellbore region where tectonic stress redistribution causes pronounced azimuthal slowness variation. This stress-induced slowness variation is important because it is also a key driver of wellbore geomechanics. Moreover, in the presence of highly laminated formations, there can be a significant azimuthal variation of slowness due to layering that is often beyond the resolution of conventional sonic tools due to their operating frequency. Finally, in horizontal wells, multiple layer slownesses are being measured simultaneously because of the depth of investigation of conventional sonic tools. This can cause significant interpretational challenges. To address these challenges, an entirely new design approach was needed. The novel pitch-catch technology operates over a wide frequency range centered at 250 kHz and contains an array of receivers having a 2-in. receiver aperture. The use of dual ultrasonic technology allows the measurement of high-resolution slowness data azimuthally as well as reflectivity and caliper images. The new LWD tool was run in both vertical and horizontal wells and directly compared with both wireline sonic and imaging tools. The inch-scale slownesses obtained show characteristic features that clearly correlate to the formation lithology and structure indicated by the images. These features are completely absent from the conventional sonic data due to its comparatively lower vertical resolution. Slowness images from the tool reflect the formation elastic-wave properties at a fine scale and show dips and lithological variations that are complementary to the data from the pulse-echo images. The physics of the measurement are discussed, along with its ability to measure near-wellbore slowness, elastic-wave properties, and stress variations. Additionally, the effect of the stress-induced, near-wellbore features seen in the slowness images and the pulse-echo images is discussed with the wireline dipole shear anisotropy processing.


2021 ◽  
Author(s):  
Thibaut Astic ◽  
Douglas W. Oldenburg ◽  
Lindsey J. Heagy

2021 ◽  
Author(s):  
Radhika Patro ◽  
Manas Mishra ◽  
Hemlata Chawla ◽  
Sambhaji Devkar ◽  
Mrinal Sinha ◽  
...  

Abstract Fractures are the prime conduits of flow for hydrocarbons in reservoir rocks. Identification and characterization of the fracture network yields valuable information for accurate reservoir evaluation. This study aims to portray the benefits and limitations for various existing fracture characterization methods and define strategic workflows for automated fracture characterization targeting both conventional and unconventional reservoirs separately. While traditional seismic provides qualitative information of fractures and faults on a macro scale, acoustics and other petrophysical logs provide a more comprehensive picture on a meso and micro level. High resolution image logs, with shallow depth of investigation are considered the industry standard for analysis of fractures. However, it is imperative to understand the framework of fracture in both near and far field. Various reservoir-specific collaborative workflows have been elucidated for a consistent evaluation of fracture network, results of which are further segregated using class-based machine learning techniques. This study embarks on understanding the critical requirements for fracture characterization in different lithological settings. Conventional reservoirs have good intrinsic porosity and permeability, yet presence of fractures further enhances the flow capacity. In clastic reservoirs, fractures provide an additional permeability assist to an already producible reservoir. In carbonate reservoirs, overall reservoir and production quality exclusively depends on presence of extensive fracture network as it quantitatively controls the fluid flow interactions among otherwise isolated vugs. Devoid of intrinsic porosity and permeability, the presence of open-extensive fractures is even more critical in unconventional reservoirs such as basement, shale-gas/oil and coal-bed methane, since it demarcates the reservoir zone and defines the economic viability for hydrocarbon exploration in reservoirs. Different forward modeling approaches using the best of conventional logs, borehole images, acoustic data (anisotropy analysis, borehole reflection survey and stoneley waveforms) and magnetic resonance logs have been presented to provide reservoir-specific fracture characterization. Linking the resolution and depth of investigation of different available techniques is vital for the determination of openness and extent of the fractures into the formation. The key innovative aspect of this project is the emphasis on an end-to-end suitable quantitative analysis of flow contributing fractures in different conventional and unconventional reservoirs. Successful establishment of this approach capturing critical information will be the stepping-stone for developing machine learning techniques for field level assessment.


Sign in / Sign up

Export Citation Format

Share Document