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Ye. A. Kopilevich and D. N. Levin, Rosneft Oil Company OJSC
One of the most promising methods for solving the problem of predicting geologic section types and reservoir permeability and porosity in crosshole space is spectral-time analysis (STAN). An innovative technology for complex spectral-velocity estimation (CSVE) in two and three dimensional crosshole space has been developed based on STAN and pseudo-acoustic transformations of seismic log data (Ye. A. Kopilevich, I. A. Mushin, Ye. A. Davydova and M. L. Afanasyev, 2000-2008); the technology makes it possible to determine geologic section types and reservoir permeability and porosity in crosshole space by a set of geophysical methods with mean accuracy of -17% (including permeability) based on subsequent drilling data. The procedure and technology for determining reservoir permeability and porosity and predicted oil productivity in two and three dimensional crosshole space are based on the use of certified seismic spectral-time attributes (STA) and seismic volume spectral attributes (SVSA), pseudo-acoustic velocities (impedances), and their integrated interpretation using modern mathematical tools: artificial neural networks (multilayer seismic perceptron) and statistical spectral correlation algorithms.

Integrated analysis of certified STA, SVSA and pseudo-acoustic velocities (impedances) using statistical spectral correlation algorithms consists of selecting statistical, correlation and gradient curves of certified SVSA and VPAC, screening types and classification methods. Integrated analysis of attributes is performed on this basis, culminating in constructing data cubes and charting geologic section types (clusters) of productive oil deposits. The basis for selection of the mathematical algorithm for artificial neural networks (ANN) for integrated interpretation is the fact that artificial neural networks controlled by sufficiently complex algorithms always produce a better result than evaluations of the discriminability of classes by simple computation procedures.

Figure 1 shows spectral-time patterns (STP) for various geologic section types of reef carbonates at the Kuyumba site compared to the corresponding lithologic columns and cross-section photographs. The parallel changes in the STP of the section types and their geologic appearance is clear. Sections with maximum development of macrofracturing are advantageous, since they preserve their basic productivity even when the procedures for opening up and testing are patently non-optimal. This group includes section types 1 and 2. The average group includes section type 3. Interlayering of dolomite, shaly dolomite, sandstone and mudstone is characteristic of this type. Reservoirs with limited development of macrofracturing type 4 were considered unfavorable. This type features both limited inflow of formation fluids and the potential for reducing the inflow in the presence of non-optimal procedures for opening up and testing. Shaly section type 5 includes mudstone which is dolomitic to various degrees. Type 6 is made up of dolomites. These are coarse carbonate deposits along sunken block edges. The presence of fracturing is typical; fissures are almost completely filled with clay materials, as is clearly visible in the cross-section photograph.

All the information presented above indicates that the nature of the distribution of seismic energy in frequency-time coordinates in STAN columns and their energy spectra is extremely specific for the different types of reef deposits (Fig. 1). This circumstance makes it possible to conclude that each section type has its own individual spectral-time pattern, which is consistent with the different lithogenetic characteristics of the section types, commercial productivity, capacity, permeability, etc. The diversity of STP makes it possible to map the development zones of the 6 distinct section types according to area and plot a corresponding chart. The chart was confirmed by subsequent drilling with an actual confidence level of more than 0.7, which is a high-quality result for such complex geological conditions.

A second example of the successful implementation of the innovative CSVE technology in a carbonate section is shown in Fig. 2, where data cubes have been constructed and charts of permeability and porosity and geologic section types have been plotted for highly prospective Lower Permian deposits in the fault-line area on the continental shelf of the Pechora Sea.

On the chart of geologic section types (Fig. 2A), the largest prospective zone, located between holes 1 and 3, matches the contours of reef seismic facies in plan. The smallest such zones which match the contours of reef seismic facies are located north of hole 3. Low-prospective and non-prospective section types are mapped in the rest of the area.


Fig. 1. Spectral-time patterns, lithologic columns, gamma-ray logging curves and cross-section photographs of six section types of carbonate reef deposits.

Fig. 2. A) chart of geologic section types of Lower Permian carbonate deposits; B) data cube of Lower Permian reservoir flow capacity.

The flow capacity distribution of horizon I(P1) (Fig. 2B) in three-dimensional space indicates significant vertical inhomogeneity, with the exception of reef bodies. It is worth mentioning that flow capacity has not been studied previously (before CSVE) based on seismic exploration data.

Hence the new geologic information obtained with the use of CSVE technology makes it possible to distinguish clearly the areas of favorable geologic section types and elevated values of reservoir properties -reef seismic facies- in two- and three-dimensional space.

The innovative CSVE technology has proven extremely effective for studying fractured Bazhenov shaly reservoirs. As we know, the study of deposits, much less prediction of their properties, based on seismic exploration data is not always feasible, and the results can be ambiguous, since there is often no persistent connection between acoustic and impedance parameters and productivity. As an example of the successful use of CSVE, Fig. 3 shows a chart of predicted oil productivity of Bazhenov deposits in the Sakhalin area (Western Siberia); three major zones of isometric form can be distinguished, located in the western, northeastern and southeastern parts of the area. The rest of the area is characterized by low prospectivity. The prediction was confirmed by subsequent drilling, with a confidence level of more than 0.7, which is a high-quality result for such an unconventional problem.


Fig. 3. Chart of predicted oil productivity of Bazhenov formations in the Sakhalin area.

Predicting the permeability and porosity of Lower Cretaceous reservoirs based on seismic exploration data and based on a combination of seismic exploration and gravity exploration was proven effective at the Vankor field (terrigenous deposits). Charts and data cubes of the porosity factor, effective thicknesses and specific volume (based on seismic exploration data and a combination of seismic exploration and gravity exploration) (Fig. 4) of Lower Cretaceous deposits (zones YaK III-VII and NKh III-IV) and a flow capacity chart (based on seismic exploration data) of NKh III-IV deposits were plotted and constructed. A correlation was identified between seismic spectral-time attributes (STA) and the permeability factor, and a data cube of the permeability of NKh III-IV reservoirs was constructed (Fig. 5); this had not been done successfully before. The basic pattern of the distribution of reservoir properties is that zones with elevated values are located on the flanks of the structure.

Fig. 4. A) NKh III-IV reservoir permeability cube; B) horizontal section of permeability cube.



Fig. 5. Charts of NKh III-IV reservoir porosity factor (A based on seismic exploration data; B based on a combination of seismic exploration and gravity exploration).

Within the Slavyansko-Temryuk petroleum zone (terrigenous deposits), seismic STA were used in combination with the VP-IP attribute (based on resistivity exploration data) to predict the reservoir permeability and porosity of Chokrak III1 deposits. Charts of the reservoir properties were plotted based on seismic exploration data, and a chart of the porosity factor was plotted based on a combination of seismic and resistivity exploration (Fig. 6). The data yielded new patterns in the distribution of zones with high permeability and porosity.

These results indicated that the innovative CSVE technology based on both seismic data and a combination of geophysical methods is highly effective for an extremely wide range of seismic geologic conditions. The CSVE technology is a new and little-known technology; accordingly, it is worth noting that its use is recommended in the "Recommended Practices for the Use of Seismic Exploration (2D and 3D) Data for Estimating Oil and Gas Reserves" approved by the Russian Federation Ministry of Natural Resources and endorsed by the State Reserves Committee in 2006.


Fig. 6. A) chart of the porosity factor of Chokrak III1 deposits based on seismic data; B) chart of the porosity factor of Chokrak III1 deposits based on a combination of seismic and resistivity exploration; C) chart of the permeability factor of Chokrak III1 deposits based on seismic data.

Labels: CSVE, Exploration, Geophysical, Porosity, Reservoir Permeability, Rosneft, spectral-time analysis, spectral-velocity estimation, STAN

posted by The Rogtec Team @ 15:00 

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