Enhancing Seismic Calibration Research Through Software Automation and Scientific Information Management

The National Nuclear Security Administration (NNSA) Ground-Based Nuclear Explosion Monitoring Research and Engineering (GNEM R&E) Program has made significant progress enhancing the process of deriving seismic calibrations and performing scientific integration with automation tools. We present an overview of our software automation and scientific data management efforts and discuss frameworks to address the problematic issues of very large datasets and varied formats utilized during seismic calibration research. The software and scientific automation initiatives directly support the rapid collection of raw and contextual seismic data used in research, provide efficient interfaces for researchers to measure/analyze data, and provide a framework for research dataset integration. The automation also improves the researchers ability to assemble quality controlled research products for delivery into the NNSA Knowledge Base (KB). The software and scientific automation tasks provide the robust foundation upon which synergistic and efficient development of, GNEM R&E Program, seismic calibration research may be built. The task of constructing many seismic calibration products is labor intensive and complex, hence expensive. However, aspects of calibration product construction are susceptible to automation and future economies. We are applying software and scientific automation to problems within two distinct phases or ''tiers'' of the seismic calibration process. The first tier involves initial collection of waveform and parameter (bulletin) data that comprise the ''raw materials'' from which signal travel-time and amplitude correction surfaces are derived and is highly suited for software automation. The second tier in seismic research content development activities include development of correction surfaces and other calibrations. This second tier is less susceptible to complete automation, as these activities require the judgment of scientists skilled in the interpretation of often highly unpredictable event observations. Even partial automation of this second tier, through development of prototype tools to extract observations and make many thousands of scientific measurements, has significantly increased the efficiency of the scientists who construct and validate integrated calibration surfaces. This achieved gain in efficiency and quality control is likely to continue and even accelerate through continued application of information science and scientific automation. Data volume and calibration research requirements have increased by several orders of magnitude over the past decade. Whereas it was possible for individual researchers to download individual waveforms and make time-consuming measurements event by event in the past, with the Terabytes of data available today, a software automation framework must exist to efficiently populate and deliver quality data to the researcher. This framework must also simultaneously provide the researcher with robust measurement and analysis tools that can handle and extract groups of events effectively and isolate the researcher from the now onerous task of database management and metadata collection necessary for validation and error analysis. Lack of information management robustness or loss of metadata can lead to incorrect calibration results in addition to increasing the data management burden. To address these issues we have succeeded in automating several aspects of collection, parsing, reconciliation and extraction tasks, individually. Several software automation prototypes have been produced and have resulted in demonstrated gains in efficiency of producing scientific data products. Future software automation tasks will continue to leverage database and information management technologies in addressing additional scientific calibration research tasks