There are practically no unexplored areas of the world left likely to hold significant oil reserves. Exploration targets these days are likely to be complex geological structures, located in remote areas with challenging climatic conditions. Gazprom Neft is developing its resources base through the implementation of cutting-edge technologies in acquiring and analysing data on the structure of oil and gas basins and specific deposits.
Prospecting for new oil reserves is a complex and high-cost endeavour, even when it involves traditional resources. The cost of geological prospecting operations, and the cost of mistakes, are higher still when investigating previously un-researched, inaccessible regions. Much of this uncertainty can be eliminated prior to commencing field work through the process of basin modelling.
Basin modelling — means taking a journey millions of years back into the past — recreating the formation of and changes to geological strata in order to determine when hydrocarbons first appeared, how they were built up, and redistributed within them.
Through this technology, on the basis of all information available on the geology of a region, mathematical and analytical methodologies are used to recreate the processes through which geological strata have been formed — and how they have been changed — meaning that areas with hydrocarbon accumulations can be laid bare.
Following construction and calibration of the basin model, the most promising blocks are selected, with a model of that field subsequently being constructed and comprehensive risk assessments undertaken, allowing the viability of developing deposits to be fully justified.
Genuinely effective and fully inclusive basin modelling tools for complex formations do not yet exist — for which reason, their development has become a key priority for Gazprom Neft’s Technology Strategy.
Seismic refraction in subsurface investigation is a key technique in modern geological prospecting, involving the artificial stimulation of acoustic waves which are subsequently registered by seismic receiversA seismic receiver
for converting mechanical oscillations into an electronic signal before the resulting seismograms are subjected to mathematical analysis and geological interpretation.
The accuracy and reliability of such investigations depends, to a large extent, on the volume of such wave sources and receivers. Until recently, however, increasing the availability of transmission and receiving points was constrained by the limitations of cable connections for the transmission of high volumes of data; a situation made resolvable through the advent of fibre-optic technology, however.
UniQ technology, developed by Schlumberger and introduced into Russia by Gazprom Neft at its Vakunaisky block at the Chonsky project, Eastern Siberia, the volume of active data-transmission channels can reach up to several hundred thousand — significantly greater than under traditional methodologies.
The very significant benefits of higher-density seismic acquisition at the company’s Eastern Siberian fields has been made possible by combining UniQ data with information sourced through cutting-edge technologies in geoelectrical prospecting.
Various electromagnetic methods are widely used in all stages of prospecting, exploration and production and field development, due to its high efficiency and relatively low cost.
The high-density of transient electromagnetic (TEM) points and transmission loops places modern geoelectrical prospecting among 3D technologies. Prospecting undertaken by Gazprom Neft at fields at its Chonsky project in 2014,moreover, is the most extensive in the world to date in terms of the physical number of TEMs utilised (more than 7,600), as well as the record time in which the project was completed.
Combining high-density UniQ seismic and geoelectrical data has allowed further fine-tuning of geological modelling of the company’s East-Siberian fields, resulting in recoverable (C1) reserves at Chonsky Group assets being increased by 48 percent in 2015.
Green “wireless” seismic
“Green (wireless) seismic” is based on the RT System 2 wireless radio-telemetry datalogging system. Gazprom Neft’s first usage of such seismic investigations took place at the Shakal block, Iraq, where the use of wireless sensors has simplified the process of installing equipment in such mountainous terrain.
The possibility of using such technology in inaccessible regions has given rise to the idea among Gazprom Neft specialists that its usage in Siberia could allow seismic operations to be undertaken in a way that is not only more effective, but also more environmentally friendly.
Compact wireless recording equipment can usually be delivered to its target location without the need for special heavy vehicles, which typically require forestry clearance to a width of at least four metres in order for them to get through. Green seismic technology, however, requires clearance of only one to 1.5 metres. On which basis, not using cables allows a two-fold reduction in forestry clearance — with the information obtained, moreover, being no less accurate that that obtained through traditional seismic works. Technologies are now being successfully utilised at Gazprom Neft assets and facilities in the Yamalo-Nenets and Khanty-Mansi Autonomous Okrugs, as well as the Tomsk Oblast.
This technology has been successfully tested at Gazpromneft-Noyabrskneftegaz’s Zapadno-Chatylkinsky block in the Yamalo-Nenets Autonomous Okrug in 2014, and is now being successfully used at various of the company’s other assets.
An information system for analysing geological and production data — GeoMate — has been commissioned at Gazprom Neft. The GeoMate system brings together approximately 80 percent of all data available from the analysis of geological, geophysical and production data. Access to a single, fully comprehensive IT environment gives employees across all Gazprom Neft subsidiaries direct and immediate access to all data in building field models and identifying and detailing promising zones and formations.
A “Digital Core” project is planned for implementation as part of the development of the GeoMate system. Supported by machine learning, this will allow the construction of 3D-drill-core models on which mathematical experiments can be undertaken, reducing the need for lengthy laboratory research.