SEG 2017

Microseismic Data to Drive Decisions

ESG will be exhibiting and presenting at the 2017 Society of Exploration Geophysicists (SEG) Annual Meeting in Houston, Texas from September 25-28, 2017.  Stop by Booth #718 to see how ESG and Spectraseis are pushing the frontiers of microseismic acquisition, processing and analysis to drive more value from your data.

Presentation Schedule (Booth #718)

Monday September 25, 2017

Exhibition 9:00am - 6:00pm

9:50  Designing an Optimal Surface Microseismic Program: Understanding the options for acquisition and processing
Brad Birkelo, Spectraseis Inc.
12:30Downhole Microseismic: Considerations for array design and data processing to improve data quality
Jon Furlong, ESG Solutions
1:30Getting better productive reservoir estimates; using surface microseismic data to map proppant-related microseismicity
Brad Birkelo, Spectraseis Inc.
2:50Characterizing Fracture Connectivity: Assessing DFN Flow Characteristics Using SMTI, Topology and Percolation
Ted Urbancic, ESG Solutions

Tuesday September 26, 2017

Exhibition 9:00am - 6:00pm

9:50  Characterizing Fracture Connectivity: Assessing DFN Flow Characteristics Using SMTI, Topology and Percolation
Ted Urbancic, ESG Solutions
12:30Getting better productive reservoir estimates; using surface microseismic data to map proppant-related microseismicity
Brad Birkelo, Spectraseis Inc.
1:30Seismicity Monitoring: How design decisions control how accurately you can determine the depth of induced seismicity
Marc Lambert, Spectraseis Inc.
2:50Designing an Optimal Surface Microseismic Program: Understanding the options for acquisition and processing
Brad Birkelo, Spectraseis Inc.

Wednesday September 27, 2017

Exhibition 9:00am - 4:00pm

9:50  Getting better productive reservoir estimates; using surface microseismic data to map proppant-related microseismicity
Brad Birkelo, Spectraseis Inc.
12:30Seismicity Monitoring: How design decisions control how accurately you can determine the depth of induced seismicity
Marc Lambert, Spectraseis Inc.
1:30Designing an Optimal Surface Microseismic Program: Understanding the options for acquisition and processing
Brad Birkelo, Spectraseis Inc.
2:50Downhole Microseismic: Considerations for array design and data processing to improve data quality
Jon Furlong, ESG Solutions
3:30Oral Paper: Room 362D 
Stimulated Reservoir Volume Estimated from Microseismicity Recorded at the Surface: A case study from the Eagle Ford

Thursday September 28, 2017

Workshop 2: Can Microseismic Moment Tensors help with the prediction of production performance of hydraulically induced fracture networks?

3:00  Keynote: The case for using MTI solutions for qualitative production prediction
Ted Urbancic, ESG Solutions

Booth Presentation Abstracts

Designing an Optimal Surface Microseismic Program: Understanding the options for acquisition and processing

Surface microseismic has progressed significantly in the last decade, perhaps even to a point where it is safe to say that the various acquisition methods (i.e. radial, patch and grid) often yield similar event locations.  There are many elements to consider when designing a surface microseismic program that may have direct implications for the quantity, quality and type of data that is acquired and it is important that operators be comfortable discussing these elements with microseismic vendors during the program design.  Here we attempt to describe the primary factors contributing to a successful surface microseismic program, focusing on the strengths and limitations of various instrumentation, the size and pattern of deployment, geological factors, considerations in sampling the full focal sphere and variations in processing methodology.  By asking the right questions in advance, it is hoped that operators can ensure an optimally designed array, and therefore have more confidence in their resulting surface microseismic data.

Getting better productive reservoir estimates; using surface microseismic data to map proppant-related microseismicity

The size of effective stimulated reservoir volume (eSRV) is considered a critical factor in assessing the effectiveness of a fracture treatment, however attempts to quantify SRV using microseismicity has historically over-estimated this volume.  Here we present a case study using surface microseismic data for hydraulic fracture stimulation of two wells in the Eagle Ford.  Using event locations and origin times of microseismic events along with pumping data, events were classified into “fracture wing” and “proppant placement” events, where the subset of proppant placement events is considered an indirect indicator of where proppant banks have been placed in the formation and can be used to estimate the minimum extent of eSRV.  Microseismic-derived estimates of eSRV show approximately 30% difference between the two wells, which is consistent with initial production rates observed for the two wells.

Characterizing Fracture Connectivity - Where is my Production Coming From?

Analysis of microseismic data for hydraulic fracture stimulations contains a wealth of information besides typical event locations and magnitudes.  Using advanced methods such as seismic moment tensor inversion (SMTI) or focal mechanism solutions (FMS) it is possible to reconstruct a discrete fracture network (DFN) providing insight on fracture orientations, failure mechanisms and rupture characteristics.  Using new approaches to describe network complexity and connectivity, volumetric network complexity can be developed to identify zones of enhanced production.  Interestingly, the derived DFN and its growth characteristics appear to be related to the ability to stimulate bedding-parallel fractures.  We examine a case study from a North American shale play focusing on containment and production from the perspective of generated fracture connectivity in order to answer the question, where is my production coming from?

Seismicity Monitoring: How design decisions control how accurately you can determine the depth of induced seismicity

Knowing the exact hypocenter depth of observed seismicity is important to properly characterize source parameters and to better understand the processes that caused an earthquake. Moreover, in the context of induced seismicity monitoring, regulations can require a minimum hypocenter location accuracy, which is typically mostly controlled by depth uncertainty. Unfortunately, hypocenter depth is the most difficult location parameter to determine with a station network located at the earth surface. In this presentation, we highlight the importance of using an optimal array design in conjunction with accurate local velocity information to locate seismicity accurately in depth. In practice, a trade-off must be expected between improved depth accuracy and the costs associated with operating the seismic station network. However, if taken into account properly, these factors allow for designing local monitoring arrays that provide customized seismicity information that is considerably more useful and potentially reliable to operators compared to data typically available from governmental or academic open sources.