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Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
Structure-metric method FOR  PREDICTIVE ESTIMATION  of NATURAL RESOURCES
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Structure-metric method FOR PREDICTIVE ESTIMATION of NATURAL RESOURCES

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Research Company offers performing forecast and estimation of presence of hydrocarbon fields by structurometric method. Structurometric method requires no field trips and provides significant time …

Research Company offers performing forecast and estimation of presence of hydrocarbon fields by structurometric method. Structurometric method requires no field trips and provides significant time saving. Forecasts developed by structurometric method, in comparison with conventional exploration activities 3 times are more exact, by 1-2 orders more efficient, environment remains undisturbed.
Root-mean-square errors of definition of deposit depths and thickness of oil and gas formation according to numerous test wells do not exceed 4-5 % (at depths up to 4000 m.). There can be discovered productive formations at depths of 7 km and more, and also on a shelf at sea depth up to 450 m.
This method can be used rather productively by investors with the purpose of predictive estimations of resources of licensed sites and areas offered for right of land tenure.

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  • 1. Research Company offers performing forecast and estimation of presence of hydrocarbon fields by structurometric method. Structurometric method requires no field trips and provides significant time saving. Forecasts developed by structurometric method, in comparison with conventional exploration activities 3 times are more exact, by 1-2 orders more efficient, environment remains undisturbed. Root-mean-square errors of definition of deposit depths and thickness of oil and gas formation according to numerous test wells do not exceed 4-5 % (at depths up to 4000 m.). There can be discovered productive formations at depths of 7 km and more, and also on a shelf at sea depth up to 450 m. This method can be used rather productively by investors with the purpose of predictive estimations of resources of licensed sites and areas offered for right of land tenure.
  • 2. SEQUENCE of RESEARCHESSEQUENCE of RESEARCHES А. Predictive zoning. Report is a skeleton map of general predictive estimate of minerals (oil and gas potential, ore minerals, water storage, construction materials) of the study area in scale 1:100000 (or 1:500 000) with drawing boundary and preliminary forecast of general sizes of all probable reserves for all specified subdistricts of the study territory.
  • 3. B. Defining perspective mineral deposits Report is a skeleton forecast map for areas of mineral bedding in scale 1:500 000 (1:200 000) with characteristic for each perspective deposit: - deposition areas, - net thickness of productive formations, - reservoir volumes.
  • 4. C. Mediumscale predictive estimation and quantitative characteristics of mineral deposits. Report -documents are a skeleton map of specified predictive estimations of minerals structures in scale 1:200 000 (1:100 000), text explanatories and tables. Productive formations serve as objects of predictive modelling and mappings. For each productive formation there created skeleton maps: - absolute deposit depth of productive formation roof; - net thickness of formation. Besides, there created a summary geologic profile showing absolute depths and net thickness of each productive formation. Scale and general number of skeleton maps made for each structure or a licensed site, depend on the area of mineral deposits and number of productive formations.
  • 5. D. Large-scale predictive estimation and quantitative characteristic of hydrocarbons fields   Report documents are detailed maps of predictive estimations of structures  perspective  for  mining operations  (scale  1:10  000  -  1:50  000),  and  also  geologic  profiles. These  maps,  profiles,  texts  and  tables  give  the  specified  predictive characteristic of separate, most perspective sites of the discovered  structures, corresponding by the contents to results of works on 3-rd stage In  addition,  in  coordination  with  customers  there  created  maps  and  tables  giving an estimation of different variants of planning of sufficient minimum  of  seismic  works  and  an  estimation  of  different  variants  of  location  of  boreholes, prospecting shafts, grooves
  • 6. Stages of works. The 1 stage. Collection and preliminary analysis of initial data.   1.1.  Purchase  of  overview  and  detailed  digital  space  photos  of  a  region  («LANDSAT»), («КАFА-1000»). 1.2. Preliminary visual decoding of overview and detailed space photos. 1.3.  Preliminary  analysis  of  literary  and  fund  cartographical  and  geological- geophysical data on area and the nearest holes drilled for oil and gas.
  • 7. The 2 stage. Preparatory mathematical structurometric modelling and predictive interpretation of complex of geological-geophysical data on the key wells and space photo.   Digital image obtained from a spacecraft of series " LANDSAT " with resolution  of 40 m (658x475 pixel) in 3 zones is used.   2.1. Preliminary gradational and structurometric correction of an image field. 2.2. Definition of a background grid of abnormal structures. 2.3. Planar filtration of the abnormal structural image with purpose of revealing  sings of hydrocarbon fields at depth from 2 up to 5 km. 2.4. Formation  of a  primary  3-dimensional matrix of anomalies of hydrocarbon  content  in  the  size  312  thousand  pixel  (in  area  extend)  х  100  pixel  (in  profile  depth).
  • 8. The 3 stage. Computer structurometric modelling and predictive interpretation of characteristics of the top and bottom productive formations. It is carried out by results of previous stage of modelling stated in the item 2. It  includes processing of the 3-dimensional matrix in the size 312.5x3 thousand  pixel (in area extent) х 100 pixel (in profile depth)   3.1.  Predictive  computer  modelling  of  thickness  of  the  top  and  bottom  productive formation 3.2. Predictive modelling of depth of the top and bottom productive formation 3.3.  Predictive  modelling  of  porosity  of  the  top  and  bottom  productive  formation 3.4.  Predictive  modelling  of  permeability  of  the  top  and  bottom  productive  formation
  • 9. The 4 stage. Digital mapping results of computer structurometric modelling and predictive interpretations of characteristics of the top productive formation.   It is carried out by results of the mathematical processing stated in the       item 3. Raster images in the size 17 thousand pixel was converted to vector  model in the size 32.9x23.7 cm (7.8 sq.dm) within the program                     « Surfer 8.04».   4.1.  Creation  of  a  digital  cartographical  basis  of  scale  1:80  000.  It  is  performed by scanning a topographical map and adding results of thematic  decoding of space image to its contents. 4.2. Creation of digital maps of thickness of the top and bottom productive  formations. 4.3.  Creation  of  digital  maps  of  depth  of  the  top  and  bottom  productive  formations. 4.4. Creation of digital maps of porosity of the top and bottom  productive formations. 4.5. Creation of digital maps of permeability of the  top and bottom productive formations.
  • 10. The 5 stage. Analysis of the maps made. Specification of the program of subsequent structurometric and cartographical works.
  • 11. The 6 stage. Carrying out of the second stage of mathematical structurometric modelling with use of complex of geological-geophysical data by the key wells and computer decoding of space photo obtained by means of the camera КАFА-1000 with resolution 20 m – 183.8 thousand pixel in 3 zones: 6.1. Preliminary gradational and structurometric correction of an image field. 6.2. Definition of a background grid of abnormal structures. 6.3. Planar filtration of the abnormal structural image with purpose of revealing  signs of hydrocarbon fields at depths from 2 up to 4 km. 6.4. Formation of a primary 3-dimensional matrix of anomalies of hydrocarbon  contents in the size 183.8x3 thousand pixel (in area extent) х 200 pixel (in profile  depth).
  • 12. The 7 stage. Computer structurometric modelling and predictive interpretation of characteristics productive formations   It is performed by results of previous stage of modelling stated in the item 6. It  includes computer processing (by number of formations) 3-dimensional matrixes  in the size 183.8x3 thousand pixel (in area extent) х 100 pixel (in profile depth):   7.1. Predictive computer modeling of productive formation thickness. 7.2. Predictive modeling of productive formation depth. 7.3. Predictive modeling of productive formation porosity. 7.4. Predictive modeling of productive formation permeability.
  • 13. The 8 stage. Digital mapping of results of computer structurometric modelling and predictive interpretations of characteristics of four productive formations on the territory of the Mayor square. It is preformed by results of the mathematical processing stated in item 7. Raster images in the size 183.8 thousand pixel is converted to vector model in the size 30.7x25.1 cm (7.7 sq.dm) within the program " Surfer 8.04" 8.1. Creation of a digital cartographical basis of scale 1:30 000. It is carried out  by scanning a topographical map and adding results of thematic decoding of the  space image to its content: 8.2. Creation of digital maps of productive formation thickness. 8.3. Creation of digital maps of productive formation depth. 8.4. Creation of digital maps of productive formation porosity. 8.5. Creation of digital maps of productive formation permeability.
  • 14. The 9 stage. Analysis of the maps made. Specification of the program of finishing structurometric and cartographical works.
  • 15. The 10 stage. Integrated computer structurometric modeling of cost-effectiveness of industrial oil-field development.   It is performed by results of previous stage of modelling stated in  the item 8. It includes computer processing of four (by number of  formations)  3-dimensional  matrixes  in  the  size  183.8x3  thousand  pixel (in area extent) х 100 pixel (in profile depth). 
  • 16. The 11 stage. Synthetic computer estimation of cost-effectiveness of location of prospecting and operational wells.   It is performed by results of previous stages of modelling stated in  the items 8  and 10. It  includes  computer  processing  of four  (by  number  of  formations)  three-dimensional  matrixes  in  the  size  183.8x3  thousand  pixel  (in  area  extent)  х  100  pixel  (in  profile  depth)
  • 17. The 12 stage. Digital mapping of results of computer structurometric modelling and predictive interpretations of cost-effictiveness of industrial oil-field development and location of prospecting and operational wells.      It is performed by results of the mathematical processing stated in  items the 10 and 11. Raster images in the size 183.8 thousand pixel  is converted to vector model in the size 30.7x25.1 cm (7.7 sq.dm)  within the program  «Surfer 8.04».
  • 18. The 13 stage. Computer estimated predictive characteristic of oil stocks by ranges of productive formation thickness. It is performed by results of previous stages of modeling and mapping, stated in the items 7 and 8. It includes computer processing (by number of formations) three-dimensional matrixes in the size 183.8x3 thousand pixel (in area extent) х 100 pixel (in profile depth).
  • 19. The 14 stage. Preparation of an explanatory note about performance of scientifically-practical work. 
  • 20. APPLICATION OF THE STRUCTUROMETRIC ANALYSIS OF AERIAL AND SATELLITE IMAGES FOR THE FORECAST AND ESTIMATION OF HC POOLS AND MINERAL DEPOSITS Testing of the Method   Application  of  the  structurometric  analysis  of  remote  sensing  data  for  the  forecast  and  estimation  of  hydrocarbon  fields  was  tested  on  various  aerial  and  satellite  imaging  data.    Black-and-white,  color,  and  spectrozonal photographs and scanned, thermal, radar, and other images of the Earth’s surface including shelf  zones with a sea depth up to 200-400 m were used. The  practical  testwork  was  conducted  chiefly  for  the  territory  of  the  Russian  Federation:  West  Siberia,  northern European  Russia, the Urals, the Volga region, North Caucasus, Central regions, Russian Far East,  and the Kaliningrad Oblast. In addition, the method was tested on the petroliferous regions of Kazakhstan,  Kirgizia, Japan, the Republic of Korea, US, Canada, Mexico, Paraguay, and Costa Rica. In the course of work,  the possibility to use the forecast models for the solution of diverse problems related to the forecast and comprehensive characterization of license areas and individual oil and gas pools was confirmed. The structurometric analysis proved to be efficient for the strategic purposes such as the petroleum zoning of large territories (regions, republics, and countries). A case in point is the forecast of the petroleum potential  of the Devonian deposits within the Astrakhan Arch, where   several ultradeep wells were planned to be  drilled.  The forecast maps and cartographic models created by the structurometric analysis technique can be used for  petroleum exploration in the vicinity of the existing, constructed, and planned gas and oil pipelines.  The discoveries resulting from this purposeful exploration can provide a significant alimentation to the fuel  flows and raise the economic efficiency of  pipeline operation. 
  • 21. Structurometric analysis enables a purposeful oil and gas exploration in regions deficient in fossil fuels. An example  is the prognostic estimate of the petroleum potential of the Tula  Oblast. The obtained data can as well be used for the planning of underground gas storages. A broad spectrum of the possible applications of  structurometric data is primarily due to  the  fact  that  clients  get  ready-to-use informative materials  such  as photographic  maps,  geological sections, tables, and other graphics rather than raw aerial and satellite  images, on  which  hydrocarbon fields are still to be found and the required characteristics are still to be  determined. All of them are created with a due regard to the consumers’ wishes and contain  the required comprehensive and fairly reliable forecast data sufficient to substantiate the launching of prospecting, exploration, and other activities in any particular area throughout the world.   This  method  requires no field trips  or  preliminary  field  surveys  and  can  be  applied  successfully even in the absence of geological or any other information. It can be applied not only in mature petroleum provinces, but also in frontier regions of the Earth.
  • 22. This  unique  method  is  particularly  attractive for the clients,  because  its  economic efficiency is much higher than that of all customary methods, including gravity, seismic, and  magnetic surveys and exploratory drilling. Using,  in  fact,  nothing but remote sensing data  even  for  a  frontier  (preliminarily  unexplored)  territory  interesting  for  the  client,  a  rough-and-ready forecast of its petroleum and mineral potential can be given and  the volume, depth of occurrence,  and  other  parameters  of  mineral  deposits  can  be  estimated  including  the  relative  difficulty  of  vertical drilling conditions and recommended well locations.  Another  sphere  of  application  of  the  structurometric  analysis  is  the  appraisal and improvement of exploration data,  including  seismic  and  drilling  data  (extension).  The  forecast of petroleum productivity in the Kaliningrad region can serve as an example. The  obtained data indicated the occurrence of many potentially petroliferous structures in that  territory, which could not be identified by conventional methods. Some of them are much  larger than the explored HC fields.  The Lukoil company furnished seismic and exploratory drilling data on a structure in which  a well (one of the four) discovered and tapped a presumably 10-meter-thick oil reservoir.
  • 23. Our  analysis  showed  a  probable  existence  of  two  more  thinner  reservoir  units  within  this  potential  structure  and  a  possibility  to  tap  the  lower  unit  by  well  no.  10  that  had  been  considered  dry, and another oil pool of commercial significance was identified to the west of  that structure. The  work  on  the  territory  of  Eastern  Kazakhstan  proved  the  applicability  of  the  structurometric analysis to the exploration of thin stacked oil and gas reservoirs interbedded  with  multiple non-commercial HC-saturated beds.   It was confirmed later by the analysis of  multi-pay oil and gas fields in the Orenburg Oblast,  South Sakhalin,  and Komi Republic. Another  advantage  of  the  method  is  the  possibility  to  apply  the  structurometric  analysis  procedure  for  offshore HC exploration.  It  was  tested  by  predictive  HC  appraisal  and  mapping  in the Caspian, Baltic, Japan,  and Yellow seas, near the western coast of Canada,  and in the Gulf of Mexico.  All  our  clients  were  satisfied  by  the  forecast  estimates.  The  geologists  that  adhere  to  customary methods were often surprised and even fazed by the accuracy of the forecast, and,  being sceptic about the results, hardly ever accepted them. The report on the investigation and analysis of geological structures at six well sites in the  Gulf of Mexico (under a contract between the Moscow State University and Global Drilling  Investigation Co Ltd., Gibraltar) was subjected to a particularly biased revision.  The final  report was submitted to a special examination. 
  • 24. Formerly, the scarcity of evidence for the successful application of remote sounding methods  in HC and mineral prospecting led many scientists to doubt the possibility to obtain reliable  and versatile data on mineral resources from satellite images. Disagreement with such a skeptic point of view induced a group of scientists of the Moscow  State  University  to  undertake  the  development  of  an  original  system  of  algorithms  for  the  structurometric analysis of multispectral satellite images with the purpose of HC and mineral  exploration and a comprehensive estimation of the deposits. The  structurometric  analysis  came  into  being  several  decades  ago  as  a  method  of  geomorphologic interpretation  of  the aerial and satellite images of the Earth’s surface. At present, the experience of investigations enabled us to establish a new mechanism for a  task-oriented recognition of various areal or structural features from remote sensing data.   A  systems-based  methodology  of  structurometric  analysis  was  developed  and  a  universal  methodology  of  computerized  scientific  analysis  and  forecast  of  the  location  and  other  parameters of oil and gas pools and other geological objects located as deep as 10 km and  even more was created.
  • 25. Fundamentals of the Structurometric Analysis of Remote Sensing Data. The structurometric analysis, like seismic methods, is based on computerized interpretation of seismoacoustic signals arriving from the Earth’s interior. Seismic methods employ the signals produced by artificial seismic impact on the crust (explosions). Based on the analysis of the travel times and patterns of the waves reflected from rock strata, seismologists determine the depth of occurrence of rock seams with certain reflecting properties and thereby predict the presence or absence of HC reservoirs. The structurometric analysis is also based on the interpretation of the data related to the travel of seismoacousting waves through the Earth’s interior. But this method, unlike seismic sounding, does not require field surveys and does not exert a harmful active seismic impact upon the Earth’s interior. The structurometric analysis is based on computer interpretation of the natural seismoacoustic waves of the Earth, indirectly reflected in remote sensing data. The sources of these waves are the deep subsurface zones of the Earth, which emit seismoacoustic waves continually, year by year. Upon reaching the Earth’s surface, these waves transform it to a certain extent. Special computer analysis enables the determination of the depth of signals arriving from rock seams with different properties and distinguish the waves arriving from HC reservoirs.
  • 26. The possibility to forecast oil and gas reservoirs from surface traces is provided by a cumulative effect of seismoacoustic waves continually arriving from oil and gas reservoirs over thousands and millions of years. Continuous radiation gives rise to more or less distinct ring and linear structures and geopathogenic zones with specific geophysical properties, reflected in remote sensing data. However, all these phenomena, resulting from the influence of oil and gas fields, are reflected on satellite images in a hidden, indirect form. Therefore, their recognition requires a number of complex procedures of computer-based structurometric systems analysis. The basis of the structurometric analysis of HC reservoirs is the recognition of the contact between the pay zone and the caprock (the rocks in the roof of oil and gas reservoirs). The zone of contact between rocks with different capacity for emitting seismoacoustic waves is the main target of structurometric analysis. The recognition of this zone enables one to study the changes in seismoacoustic waves as they travel through the contacts between rocks with different physical properties and determine the depths at which these changes are detected. Each contact zone shows an individual pattern of effect upon the surface, which is superimposed upon the patterns of other contacts at different depths. Therefore, each part of the Earth’s surface bears a vast number of ring structures and traces of the effect of the Earth’s interior upon its surface. Consequently, the traces of effect of each rock seam on satellite images are usually masked and indistinct, because each of them overlaps the effects of other seams.
  • 27. The objective of scientific investigation is the search of the criteria enabling one to reliably distinguish the signals corresponding to petroliferous rocks and ignore a multitude of other signals arriving from the rocks that do not contain oil or gas reservoirs in conditions of the studied sector of the Gulf of Mexico. This is possible only if the structurometric analysis employs specially adjusted fine computer procedures, which enables one to detect even the weakest and disguised seismoacoustic signals, perform their computer processing, and thereby determine the depth of occurrence, thickness, composition, and other properties of the studied rocks. The structurometric analysis becomes particularly difficult when applied, e.g., to offshore areas, very deep occurrence of pay zones, and the stacked reservoirs within the presumably petroliferous structures. The seismoacoustic waves grow increasingly distorted and transformed with distance from the source as they travel from the deep crustal levels to the surface. The extent of distortion of the primary seismoacoustic waves depends on rock properties variation in the sequence and the number of oil reservoirs. An increase in the latter leads to an increase in the number of interfaces between rock masses with contrasting properties, reflected on satellite images.
  • 28. Brief Description of Analysis Procedure The structurometric analysis of remote sensing, cartographic, geological, and other data includes some complex technological procedures, new software, and sophisticated intellectual resources. The methods and techniques of aerial and satellite image processing, computerized interpretation, and cartographic modelling are arranged into a single algorithmic system. The system employs various software products: original program-algorithmic blocks, commercial geoinformation systems, and special graphic modules that enable one to combine conventional geologic mapping with a multiparameter three-dimensional graphics etc. The whole integrated system of programming techniques and the main features of the applied software are ORIGINAL and HAVE NO EQUIVALENTS IN WORLD PRACTICE. The necessity to work out and apply a wide spectrum of special sophisticated programs is caused by the extreme difficulty of the recognition and reliable identification of HC pools based on remote sensing data, which are not directly reflected in the structural features of the Earth's surface.
  • 29. Our experience of investigations suggests that it is impossible to obtain information related to HC exploration by means of a single, even most complicated and universal program. Therefore, a number of software module workflows were created. Application of these workflows enables one to gradually pass from one task to another. For instance, even the initial aerial and space image processing employs the following software modules: programs for preliminary gradation and structurometric correction of the picture field; piecewise Fourier transform of the picture, enabling one to detect regions with the lowest amplitudes of the harmonic components of the initial picture; screening of the initial structural picture, i.e., its transformation into binary form using the Evans algorithm that detects regions with a negative Gaussian curvature; recognition of the background network of ring structures (numbering tens and hundreds of thousands in a square kilometer), whose mutual onlapping and combinations produce an intricate interference pattern; matched filtering of the binary structural picture aimed at the recognition of ring and elliptical structures corresponding to HC pools etc.
  • 30. Estimations of Undiscovered Resources of Hydrocarbon Raw. An estimation of undiscovered resources of hydrocarbon raw is realized in three steps. Each of the step differs from others, having a different level of both detailedness of the initial space information, and, hence, detailedness of the resulting estimations. On the preliminary stage of research, the reference space data of 1: 200000 -1:1000000 scale (MSU-SK instrument, "RESURS-O" satellite [3-5]) is used. The data prosessing results in: • estimation total productivity of oil resources for a specified territory, with a preliminary estimation of oil reserves (mill, ton), gas (bill.cu.m.), gas condensate (mill, ton); • pre-forecast (first-step iteration) of the potential area of fields, containing hydrocarbon raw, with estimations of: - sizes of oil, gas and condensed gas deposits (mill, ton; bill.cu.m.); - depths (relative and absolute values) of productive strata (m); - thickness of strata(m); - concentration of hydrocarbons per stratum (%).
  • 31. At licencing activity of plots, the reference space data of 1:50000 -. 1:1000000 scale (MSU- E instrument, "RESURS-O" [3-5]) is processed. As a result, the following information is available: • forecast (second iteration) of potential structures, containing hydrocarbon raws, with estimated: - boundaries of potential pays (commercial deposits); - volumes of oil, gas and condensed gas deposits (mill, ton; bill.cu.m.); - depths (relative and absolute values) of productive stratum roofs (m); - thickness of strata(m); - concentration of hydrocarbons per stratum (%); - quality properties of hydrocarbon raws (density, content of sulfur, paraffin's, etc.).
  • 32. To ensure drilling operations, at the preparation activity phase the reference data of 1: 5000 - 1: 10000 scale (MK-4, KFA-1000 instruments, "RESURS-F" [6, 7]) must be processed. The activities will result in: • forecast (third iteration) of potential structures, containing hydrocarbon raws, with estimated: - precise boundaries of potential pays (for each productive stratum); - volumes of oil, gas and condensed gas deposits (mill, ton; bill.cu.m.) - total and for each productive stratum; - depths (relative and absolute values) of productive stratum roofs (m); - thickness of each stratum (m); - the concentration of hydrocarbon for each stratum (%); -quality properties of hydrocarbon raws (density, content of sulfur, paraffins, etc.) for each stratum and a specified unit of explored structures; • recommendations on the arrangement of drill holes with taking into account the above estimations and a forecast on environment and on-site geophysical conditions (including effect of fractures and geo-nosogenic structures, occurence of local seismicity regions, geochemical anomalies etc.)
  • 33. Validation of the Technique for Oil, Gas and Minerals Exploration. The efficiency of the proposed technique was validated with tjie results of a pilot ground survey of a territory within the Satinsk range (Kaluga oblast, Russia) of Geographical faculty of Lomonosov MGU Kaluga oblast, Russia) (fig. I). At present, -it should be emphasized as an advantage of the technique- it is already essentially developed and has passed a serious tests during the imagery analysis executed for a number of regions in Russia (Kaliningrad Oblast, fig. 2-3, table 1-2), east Kazakhstan and Canada. Such a domestic oil giant as LookOil company has shown her interest to the technique. By order of that company a’ detail mapping was carried out for the company's territories that confirmed the deposits, found out early, and revealed new beddings and flat-lying stratums of oil.
  • 34. Results of the relief mapping of parent materials, a territory within the Satinsk range (Kaluga oblast, Russia) of Geographical faculty 'of Lomonosov MGU, on the basis of a picture of annular structures: a - current relief in the topographic map of 1:10 000 scale; б - parrent relief in the topographic map of 1:25 000 scale, resulted from drilling data; в - parrent relief, designed by Yu.I. Fivenskiy under the annular structures. Fig. 1
  • 35. So, there are potential customers for space prospecting information, acquired by specialized facilities and properly processed. The submitted technique for structural analysis is a validated tool that is available to meet the market requirements.  3-13 sites, recommended for wells (if 13 wells - 53.7% recovery of deposits). 5 and B are the top-priority sites, recommended for wells. Fig. 2 Fig. 2
  • 36. Onboard Spectrometric System' for Prospecting. So far, the said technique was tested mainly on the aero-survey data. However, the technique will provide higher cost efficiency if it uses space information of earth remote sensing systems. The higher spatial and spectral resolution of satellite imagery is, the more sophisticated structure analysis of beddings and, hence, the more accurate forecast and estimations of natural resources will be available under the technique. Being based on the space survey data only, the approach will give an opportunity to solve the economic problems mentioned above (in particular, exploration and estimation of the sizes of oil-and-gas fields and other mineral deposits), with no expensive and inefficient gound-based prospecting operations. Since 1998, within the framework of the Russia Federal Space Program, activities on development of an onboard spectrometric system for prospecting have being carried out.
  • 37. Structurometric analysis of aerial and space photographs for the purpose of forecast and estimation of hydrocarbon fields is based on the patent No 02- Д/02 'Minor ring-shaped structures of friable deposits of the Earth's crust'.
  • 38. INTRODUCTION OF NEW INTEGRATED TECHNOLOGY (structure-metric method) FOR PREDICTIVE ESTIMATION of NATURAL RESOURCES, On the basis of the system computer analysis of figures of earth remote sensing and use of properties of small ring structures
  • 39. Stated below concrete results illustrate application of new technology:  1. Under the request of company " Lukoil " a test development, under their application of a single-layer "Olympic" structure of the Kaliningrad area of Russia (Fig.1) is executed. Fig.1
  • 40. On fig. 2 results of our forecast of a deposit of this layer which detail of study essentially differs, and the resulted depth of occurrence corresponds to results of drilling. fig. 2
  • 41. Besides that through our research it has been shown, that «Olympic» structure is double-layer and the second layer is on 10-12 meters below the upper a productive layer (as customers considered - the only thing). We have revealed also, that their second, so-called "empty" well №3 has appeared to be productive after additional drilling. These materials are presented by us (Sadovnichij V.A., Utkin V.F., Zhukov V.T., Lazarev G.E., Fivenskij J.I., etc.) in the report on small satellites in USA. fig. 3
  • 42.           2. Under the request of industrialists of the Mexican United States has been executed the predictive estimation of deposits of hydrocarbons for area of two installed platforms in gulf of Mexico. Wells, which had been drilled earlier by the customers up to depth of 6000 meters had appeared to be empty. Depth of a sea gulf in these points reached 400 m. ( Fig. 4) Fig. 4
  • 43. Our predictive estimation of structures of each deposit has shown, that wells are drilled on the edge of layers (Fig. 5). According to our development both these, significant on resources, are four-layer structures, but the drilled wells have passed outside of layers. On Fig.5 is shown an erroneous position of well 1 and coordinates of a point 11 where it is necessary to move the drilling platform . Fig. 5
  • 44.      We have executed deep research of a deposit structure (a Fig. 6) and have shown its multilayer structure.      On a contour A-B (the second section C-D has been also investigated) are shown all layers of oil field Alak and two geodynamic fractures. After studying the presented materials under the request of the Customer we had been developed another four objects with definition of installation sites for platforms in gulf of Mexico. Accounting materials have been passed to the Customer - to company «Global Drilling Investigation Co Ltd » on six points where installation of drilling platforms is recommended (See the covering letter of the Moscow State University concerning delivery of documents to the customer).
  • 45. 3. The comparative analysis of predictive estimation of hydrocarbon deposits of Timano- Pechora oil-and-gas province (See Fig. 7). Fig. 7
  • 46. The subimage of this territory shows, that predicted with the help of structure- metric method: - Deposits in 18 cases from 20 confirm the structures reconnoitered by geologists; - The borders of structures revealed by us more detailed, than shown by traditional geological prospecting which integrated cover some separate structures; so for example borders of structures in the southeast №37 and №62 revealed by us and traditional geological prospecting completely coincide; and two structures №12б and №43в, revealed by us, traditional geologists show in one structure; - Many new structures have not been revealed by traditional geological prospecting; Predicted by structure-metric method resourses of hydrocarbonic raw material, in each deposit, are accompanied by a tentative estimation of its volumes. The structures shown by traditional geological prospecting do not contain such information.  
  • 47. 4. Predictive characteristic of Vostochno-Vejakskoe deposit on the basis of structure-metric method analysis of aerospace information (See Fig. 8). Map of the deposit and the structure A-B, noted on this map. Fig. 8
  • 48. The traditional geological prospecting has detected borders of only one dome of Vostochno-Vejakskoe deposit, which are shown on the map by a continuous green line. On the presented map it is given, developed by us predictive characteristic of Vostochno-Vejakskoe deposit, convincingly showing fuller and more detailed predictive estimation of a deposit. On the map are shown the revealed new areas of the given deposit and total capacities of layers of three productive parts of this uniform structure stretching on a parallel more, than on 10 kilometers.
  • 49. Also it is presented the geological structure of Vostochno-Vejakskoe deposit. On the structure are shown effective capacity of productive layers and absolute depth of occurrence of productive layers roof . 5. As an example proving high efficiency of a method of Small Ring Structures for studying of a deep structure of an earth's crust, on fig. 9 are shown results of structure-metric definitions on arid zone (sandy desert - the United Arab Emirates). On the figure are presented results of definition of depths of occurrence of the basic lithologic borders of section of layers of sedimentary rocks in vicinities of a geological well on a ring skeleton of a two-dimensional structure in length of 2,55 km and by width ±850 m, passing its axis through the well. An initial material - the space picture Landsat-7 received in integral (izopanchromatic) zone with the sanction of 15 m on district. Structure-metric profile precisely records buried graben, not being reviled in morphology of modern district. Besides attracts attention higher detail (in comparison with a lithographic column of a well) of imagery thematically significant litilogical borders of sedimentary rocks. On the resulted profile it is shown, that if the well has been installed in 150 meters from drilled, water discharge could be essentially increased.
  • 50. Fig. 9
  • 51. Thank you for attention!Thank you for attention!

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