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Collaborating Authors
Microseismic, Inc.
Use of Automatic Moment Tensor Inversion in Real Time Microseismic Imaging
Michael, Kratz (Microseismic, Inc.) | Orlando, Teran (Microseismic, Inc.) | Thornton, Michael (Microseismic, Inc.)
Summary In this paper we evaluate the use of an automatic moment tensor inversion algorithm on passive seismic data from the Eagle Ford for its usefulness in evaluating the microseismic source mechanisms as well as potential applications for real time processing by comparing it to a hand-picked source mechanism inversion method. Hand picking involves manually picking first arrival p-wave amplitudes for a subset of events and utilizing a grid search for a pure shear or DC (double couple) strike, dip, and rake source mechanism solution (Aki and Richards, 1980). A least squares inversion (Sipkin, 1982) is utilized for the full moment tensor solution. This provides a general fit solution that is representative of all events. The solution fit is verified by applying polarity reversals to correct for the radiation pattern at the surface such that the first p-wave arrival becomes consistent. This is repeated until enough general solutions exist to properly correct move-outs for all events, classifying them into discrete mechanism groups. Automatic picking utilizes a form of full waveform inversion to calculate moment tensors for every microseismic event individually. The dataset analyzed in this paper exhibited two distinct source mechanism solutions from the hand picking process, one dip-slip style class of events and a strike-slip class extending away from the well as a long coherent trend. This trend was dominated by a strike slip shear mechanism solution causing it to stand out against the rest of the treatment and was interpreted as a sub-seismic fault. Clustering analysis can be used as an early alert system to show the emergence of such a fault or other geo-hazard during hydraulic fracturing operations. Automatic calculation of moment tensors offers a distinct advantage over the hand picking method in that it enables fast and efficient evaluation of numerous microseismic events and their possible source mechanisms by computer with little need for analyst intervention. While hand picking source mechanism solutions results in a small number of discrete solutions fitted to the entire point set, automatic picking offers a full moment solution for all events. This facilitates a more detailed and accurate picture of stress and resultant fracture network both spatially and temporally. It also offers a much quicker response to large changes in source mechanism in real time allowing the processing to adapt to these changes as they happen. This eliminates the need for an analyst to pull data, pick a new source mechanism, apply it to the processing, and delaying results delivery by requiring reprocessing of data. Such detailed moment tensor analysis makes it possible to quickly build more accurate discrete fracture network models, meaning that engineers can begin to plug microseismic data into their modeling in near real time in a more deterministic way. The most direct application of this type of analysis is real time stress evolution analysis. Being able to determine temporal changes in the stress fields offers a look into how the treatment is changing the stress field as its happening.
Drainage Estimation and Proppant Placement Evaluation from Microseismic Data
Neuhaus, Carl W. (Microseismic, Inc.) | Ellison, Mary (Microseismic, Inc.) | Telker, Cherie (Microseismic, Inc.) | Blair, Keith (Gastar Exploration Ltd.)
Abstract In this case study we outline how microseismic analysis can be used to optimize treatment design and determine the portion of the stimulated rock volume that should be productive. To begin, microseismic data was acquired with a permanently installed shallow buried array of geophones during the hydraulic fracturing of 17 wells in the Marcellus Shale. The processed results were used to conduct a multi-disciplinary study integrating geology, geomechanics, reservoir and completion engineering, and ultimately, production data. A stress inversion from focal mechanisms was performed, and correlations were made between hydrocarbon production and microseismic results. That work, in conjunction with the variability in the stimulation approach, was used to optimize the treatment design on an individual wellbore and on a field development scale. Treatment design analysis indicated optimum wellbore spacing, stage spacing and length as well as evaluated the vertical coverage of the treatment within the Marcellus. Incorporating information from source mechanisms, an event magnitude calibrated discrete fracture network (DFN) was modeled taking into account the seismic energy of the events, rock properties, the injected fluid volume and efficiency. Evaluating the placement of proppant inside the DFN enables distinction between the part of the stimulated rock volume (SRV) that contributes to production in the long term, and the part of the reservoir that was affected by the treatment but may not be hydraulically connected over a longer period of time. Finally, the permeability of the stimulated fracture system was calculated from the microseismic results. This allows for the evaluation of the drainage volume and estimation of production.
- North America > United States > Ohio (0.54)
- North America > United States > West Virginia (0.54)
- North America > United States > Virginia (0.54)
- (3 more...)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Structural Geology > Tectonics > Plate Tectonics (0.47)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.41)
- Geology > Petroleum Play Type > Unconventional Play > Shale Play > Shale Gas Play (0.38)
Correlation of Surface Microseismic Event Distribution to Water Production And Faults Mapped On 3D Seismic Data: a West Texas Case Study
Keller, William R. (Chesapeake Energy) | Hulsey, B.J. (Microseismic, Inc.) | Duncan, Peter (Microseismic, Inc.)
Summary The use of microseismic techniques to map hydraulic fracture treatments has increased dramatically in recent years. During this time, microseismic monitoring has grown from a technical curiosity into an established method for determining the spatial distribution and therefore effectiveness of well completions in tight reservoirs. While both surface and downhole microseismic monitoring techniques are widely used throughout the industry, surface microseismic methods have typically been met with more skepticism. We present a case study from West Texas in which surface microseismic results from two adjacent wells are validated by both 3D seismic and production data. Introduction In 2007, Chesapeake Energy re-entered the Sunray 72-3 #1 well in Reeves County, TX with the purpose of completing the well in the Barnett and Woodford shale formations. During the same time period, Chesapeake drilled the MBF 72-4 #1 vertical well to target the same formations approximately 4000 ft to the west of the Sunray. Both wells were drilled vertically to a depth of approximately 13,000 ft. Over a period of weeks, a four stage completion was performed on each well. The Sunray was completed with primarily slickwater and the MBF was completed with primarily crosslinked gel. During each frac stage, microseismic data was recorded using a dual FracStar surface array which consisted of geophones arranged in a radial pattern extending out from the well pad. The total array consisted of 18 arms with 100 ft group spacing and a maximum recorded offset of 900 feet. A total of 853 and 1925 events were recorded for the MBF 72-4 #1 and Sunray 72-3 #1 wells respectively using PSET® technology developed by Microseismic, Inc. Discussion Based on FMI data collected in these wells and several other wells in the surrounding area, the minimum horizontal stress direction in this area is constrained to be approximately N40°E. Prior to the collection of microseismic data, it was expected that the hydraulically induced events would be aligned along a roughly NW-SE azimuth, perpendicular to minimum horizontal stress. However, the surface microseismic results show vastly different event distributions for the two wells (Figure 1). The MBF 72-4 #1 distribution is relatively tightly confined around the well and shows little azimuthal preference. On the other hand, the Sunray 72-3 #1 distribution covers a much larger area and shows a strong preferential orientation roughly parallel to the minimum horizontal stress direction, perpendicular to pre-frac expectations. A conjugate NW-SE trend can also be seen in the data but is much weaker than the overall NE-SW trend. This result is extremely puzzling in the absence of 3D seismic, and indeed, the microseismic data was processed prior to delivery of the 3D seismic volume. When placed in geological context with the 3D seismic data, these microseismic event distributions become much easier to interpret. A NE-SW trending fault that extends to the Sunray well location can be easily mapped on the 3D seismic volume. This fault runs parallel to the Sunray microseismic distribution and is also clearly visible as a NE-SW trending black discontinuity on the coherence map shown in Figure 1.
- North America > United States > Texas > Fort Worth Basin > Barnett Field > Barnett Shale Formation (0.94)
- North America > United States > Oklahoma > Anadarko Basin > Cana Woodford Shale Formation (0.94)