Reservoir characterization

Method Integration Improves Reservoir-Property Prediction in East Siberia

This paper describes a case study of the Chonskaya group of fields to demonstrate an approach to the integration of time-domain-electromagnetic (TDEM) electrical and seismic data when building a geological model for improving reservoir-property and -saturation prediction.


This paper describes a case study of the Chonskaya group of fields to demonstrate an approach to the integration of time-domain-electromagnetic (TDEM) electrical and seismic data when building a geological model for improving reservoir-property and -saturation prediction.


The terrigenous sediments of the subsalt complex within the Nepa-Botuoba anteclise are characterized by complex geology: nonanticlinal traps, complex tectonics, lateral reservoir heterogeneity, and digenesis that controls reservoir distribution. The block structure of the Chonskaya group of fields and their poor coverage with exploration wells (Fig. 1) leave a number of uncertainties with regard to water/oil and gas/water contacts in blocks with proved oil content, as well as the main fluid types in exploration blocks.

Fig. 1—Block structure of the terrigenous complex. Promising blocks are marked by colors: green (a terrigenous complex), orange (carbonates), and gray (exploration blocks).


The success of predicting prospective sites for exploration drilling is influenced by minimal risks and reduced uncertainty during field development. An important task at the stage of exploration drilling is to increase the reliability of fluid contacts and reservoir properties. To improve the quality of geophysical predictions during exploration of the Chonskaya group of fields, geological exploration operations were conducted, including 3D seismic surveys and high-density electrical studies [time-domain electromagnetic and magnetic (TDEM)] on a single observation network.

The area studied by TDEM and seismic surveys on the observation network in the Chonskaya group covers 3500 km2, more than 50% of the total territory of the license areas. In this regard, the methods to honor the TDEM data when building and updating complex geological models of reservoirs are being actively developed, because the TDEM signal can provide information about fluids saturating terrigenous reservoirs.

To understand the capabilities of the technology for integrating seismic and electrical data and making a decision on the basis of the TDEM survey, forward modeling is necessary. On the basis of the modeling results and experience in building complex geological models, the combined use of electrical and seismic data has the potential to be used to separate pure-oil, water/oil, and pure-water zones; to predict probable fluid types in the exploration targets; and to outline zones with poor reservoir properties in terrigenous rocks of the subsalt complex within the Nepa-Botuoba anteclise.

A geological model honors the TDEM data through building a geoelectrical reservoir model using a priori geological and geophysical information about target reservoirs—the kinematic and dynamic interpretation of seismic data, well-log-­interpretation data, a petrophysical model, and a geological model of the reservoir (2D or 3D). Next, a comparative analysis of the synthetic geoelectrical model with the TDEM inversion data is conducted. The geological model assumptions are revised on the basis of qualitative and quantitative comparison. The revised assumptions allow reduction of the range of geological uncertainties and adjustment of the geological exploration program.

Preconditions for Use of TDEM To Determine Reservoir-Fluid Types

Block 1 is one of the project drivers. Four wells drilled in the dome part of the B13 structure produced commercial oil inflows, and another well, located much lower in the structure, produced an inflow of water. Given the gently sloping structure of the reservoir, the oil/water-contact (OWC) uncertainty (one of the key uncertainties) affects the oil-bearing area significantly and, as a consequence, the volume of initial in-place reserves.

At the initial stage, for the wells with different types of fluid (W-1 with oil and W-4 with water), a synthetic model of the TDEM signal was built. In this case, the lateral logging data were averaged to the scale of geoelectrical layers and the signal response was simulated. Next, data inversion was performed (a reconstruction of geoelectrical characteristics of the geoelectrical layer from a noisy signal).

The analysis of the reconstructed signal distribution in Wells W-1 and W-4 shows different geoelectrical properties of the target interval when the B13 reservoir is saturated with oil and with water. On the basis of the preliminary simulation, Block 1 was selected as a pilot area for the development and testing of the data-­integration technology (seismic and TDEM).

Data Integration in the Geological Modeling Process

Building a unified geological model and subsequent complex prediction on the basis of results of two geophysical methods (TDEM and seismic) requires a methodology for honoring the TDEM data in the process of building a geological model. The technology used here is robust integration of electrical and seismic data, aimed at improving the accuracy of the geological reservoir model by reducing uncertainties related to fluid contacts (OWC and gas/water contact), water saturation, and reservoir properties by building geological models that satisfy seismic and electrical survey data.

Building an integrated geological model and conducting subsequent model runs includes the following stages.

Obtaining Initial Geoelectrical Characteristics of a Reservoir. This involves inversion of TDEM data and the building of a background conductivity model of host rocks to determine lateral reservoir conductivity. As a rule, the geoelectrical layer of the target interval is more than 100 m thick. In the Chonskaya project, the geoelectrical layer is represented by the target interval of Vendian terrigenous deposits, the productive part of which consists of two reservoirs, B10 and B13, and over- and underlying mudstone units. The complete paper provides equations by which geoelectrical reservoir characteristics can be obtained.

Building a Synthetic Geoelectrical Reservoir Model.  A synthetic geoelectrical model of the reservoir is built on the basis of a geological realization. The water saturation and porosity parameters of the geological model are used, through an electrical saturation model, to determine reservoir resistivity, and the net thickness is used to determine lateral conductivity of the reservoir. The geoelectrical characteristics of the synthetic model are estimated on the basis of the input parameters. If the target complex contains two or more reservoirs, the geoelectrical reservoir models are estimated for each reservoir separately and then the integral characteristic of the lateral conductivity is determined by summing the conductivity maps of each reservoir. The synthetic model of the reservoir lateral conductivity is compared with the TDEM conductivity.

Ranking and Selecting the Geological Models. The corresponding synthetic geoelectrical models of these geological models should be ranked on the basis of their similarity to the initial geoelectrical model. This stage includes a qualitative and quantitative comparison of the simulated resistivity parameters with the lateral conductivity of the synthetic and initial geoelectrical models, which allows conclusions to be reached on the basis of the geological model correctness. The model selection criteria include a correlation coefficient and a root-mean-square deviation. Next, a set of synthetic models with the best criteria is selected.

Correction of the Geological Model With TDEM Data. To build a geological model with a high degree of correlation that satisfies the initial TDEM-based geoelectrical model, an algorithm was developed. The algorithm corrects the prediction maps for the geological realization of parameters until a minimum discrepancy is achieved between the observed and the synthetic lateral conductivity of the model. In this case, the variable parameters are assigned the variation range regulated by a priori geological and geophysical information.

The geological realizations that have the highest degree of convergence with the initial geoelectrical characteristics allow building a geological model that honors the results of two geophysical methods. Consistent development of geological realizations (consideration of various OWC levels and update of reservoir properties) allows building a geological model with minimal mis-ties of the synthetic and observed geoelectrical field.


This technique has been tested when building a comprehensive geological model of Block 1 of the Chonskaya group of fields. The geological model of target horizons is built on the basis of well data, concept modeling, and seismic and electrical exploration. OWC position is a key uncertainty in the geological model of this block.

The initial range of contact uncertainty was 15 m. The OWC variations in the geological model and a consistent quantitative comparison of the maps of synthetic and observed geoelectrical parameters allowed reduction of the estimated OWC to 5 m. The range of reserves uncertainty was reduced by 30%, and P50 reserves increased by 13 million tons. The analysis allowed relocation of the exploration well to intersect the OWC most probably and to remove OWC uncertainty completely within the block.

The results demonstrate the potential of using TDEM data when building a geological model for updating fluid type and reservoir properties in Eastern Siberia. In the context of complex geological and physical conditions, a low degree of study, and high geological uncertainties, it is recommended to integrate the seismic and electrical data that describe various physical parameters of the subsurface and, in the case of reasonable integration, complement each other. This approach allows use of geophysical data in the process of building a model for making effective decisions on field appraisal and reducing geological uncertainties, an ability of particular importance at the exploration stages of field development.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 191673-18RPTC, “Seismic- and Electromagnetic-Methods Integration To Increase Quality of Reservoir-Property and -Saturation Prediction in East Siberia Region,” by Pavel Mostovoy, Roman Oshmarin, and Andrey Ostankov, GazpromNeft, and Olga Tokareva and Daria Orlova, IERP, prepared for the 2018 SPE Russian Petroleum Technology Conference, Moscow, 15–17 October. The paper has not been peer reviewed.