Abstract

Abstract. This paper presents an integrated approach for land subsidence monitoring using measures coming from different sensors. Eni S.p.A., the main Italian oil and gas company, constantly surveys the land with all the state of the art and innovative techniques, and a method able to integrate the results is an important and actual topic. Nowadays the world is a multi-sensor platform, and measure integration is strictly necessary. Combining the different data sources should be done in a clever way, taking advantages from the best performances of each technique. An integrated analysis allows the interpretation of simultaneous temporal series of data, coming from different sources, and try to separate subsidence contributions. With this purpose Exelis VIS in collaboration with Eni S.p.A. customize PISAV (Permanent Interferometric Scatterometer Analysis and Visualization), an ENVI extension able to capitalize on and combine all the different data collected in the surveys. In this article are presented some significant examples to show the potential of this tool in oil and gas activity: a hydrocarbon storage field where the comparison between SAR and production volumes emphasise a correlation between the two measures in few steps; and a hydrocarbon production field with the Satellite Survey Unit (S.S.U.), where SAR, CGPS, piezometers and assestimeters measure in the same area at the same time, giving the opportunity to analyse data contextually. In the integrated analysis performed with PISAV not always a mathematical rigorous study is possible, and a semi-quantitative approach is the only method for results interpretation. As a result, in the first test case strong correlation between injected hydrocarbon volume and vertical displacement were highlighted; in the second one the integrated analysis has different advantages in monitoring the land subsidence: permits a first qualitative “differentiation” of the natural and anthropic component of subsidence, and also gives more reliability and coverage to each measurement, taking advantages from the strong points of each technique.

Highlights

  • INTRODUCTIONNatural component is the results of geological and geodynamic processes occurring both at regional and local scale (Johnson, 1995)

  • Land subsidence represents a complex phenomenon due to natural and anthropic causes

  • In this article are presented some significant examples to show the potential of this tool in oil and gas activity: a hydrocarbon storage field where the comparison between Synthetic Aperture Radar (SAR) and production volumes emphasise a correlation between the two measures in few steps; and a hydrocarbon production field with the Satellite Survey Unit (S.S.U.), where SAR, Continuous GPS (CGPS), piezometers and assestimeters measure in the same area at the same time, giving the opportunity to analyse data contextually

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Summary

INTRODUCTION

Natural component is the results of geological and geodynamic processes occurring both at regional and local scale (Johnson, 1995) It can be investigated by using appropriate data which belong to different geo-science disciplines (i.e. geology, geodynamics, geophysics, geodesy, climate, etc.). Vsl, and Vc, respectively tectonic, sedimentary and compaction components have long term geological effects (millions of years); Vpgr, post-glacial component is a short term geological component (thousands of years) The sum of these four factors accounts for the natural component of vertical movement. Environmental effects caused by hydrocarbon production and virtuous ethical behaviour make the distinction between natural and anthropic components inside measurements suitable. The integration with different sensors and measures (like as rainmeter, termometer, social index, etc.) could help with correct planning land management activities in order to reduce the effects of subsidence in historical cities and industrial zones (Baldi, 2009)

MONITORING SYSTEMS
Levelling
Assestimeters and Piezometers
INTEGRATED ANALYSIS
Test Area
Integrated analysis workflow
Surveying Data and integrated analysis
Results
CONCLUSIONS

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