Generally the common basin modeling workflow includes seismo-geological, sedimentological and petroleum systems models development. The integration of structural modeling and palinspastic reconstruction is required if significant lateral displacement exists in the basin (in case of extensional and compressional tectonic regimes). The article is concerned with the difference between petroleum basins with simple and complex tectonic structure as well as challenges which modern basin modeling technologies with integration of structural reconstruction allows to solve. Some examples of Gazpromneft STC projects are provided.

The article shows the need to complement the well rating assessment of the seismic structural models uncertainty. The paper presents an example of uncertainty estimation of structural models in the process of planning new wells. Implemented of the seismic model error estimation using modifications of the cross-validation method. Discussed the limitations and solutions of cross-validation in the "complete cross-validation" modification. The implemented approach has been tested on the planned wells in the Novogodnee and Vyngapurovskoe oil fields.

А variety of modern inversion techniques (including the results оf deterministic acoustic and simultaneous and stochastic simultaneous (geostatistic) inversions) are represented in the focus of its potential for use to forecast «sweet-spots» in vendian terrigenous deposits with an accurate reservoir properties estimation. Forecast was verified by two new wells. The data is a property of LLC Gazpromneft-Angara license block in Eastern Siberia.

Bazhenov fm. is one of the most important issues in the development of a new resource base to "Gazpromneft". Since recently several projects related to the oil and gas of Bazhenov fm. potential on the different scale (regional, zonal and local levels) are under development in the Company. In the framework of the regional assessment project of the Bazhenov fm. sediments (PBE) the area ranking according to the unconventional petroleum potential was carried out in 2012. The prolongation of the project in 2015 resulted in the formation of 3D petroleum system model which is unique in terms of cover area, model size and amount of input data. The model allowed for the evaluation and area ranking to be performed in the quantified manner. A detail prognosis of petroleum physicochemical properties for Bazhenov fm. was made combining petroleum system modeling methods and geochemical and physical data. Despite of long exploration history, huge petroleum potential of Bazhenov fm. and direct oil and gas manifestations a detailed assessment of the prospects was not conducted so far. A complete set of data was integrated into the model including experimental data. Primary and secondary cracking and HC migration modeling was modelled. Based on the result a number of maps was build describing petroleum potential and petroleum reserves. Gas and oil physicochemical properties depend on the OM maturity level. Using the density of oil and HC gas and gas saturation prognosis throughout the model Bazhen fm was evaluated. One of the main results of the work was the proposal of additional search parameter for assessing the prospects of the Bazhenov fm.

Currently oil companies are focusing more on hard-to-develop oil fields with high geological uncertainties. To develop these fields efficiently we need a sophisticated geological risk management and advanced techniques for exploration program optimization. However, having many different uncertainties poses a big challenge as it is almost impossible to completely eliminate uncertainty. In this paper we show how to build a tool to estimate economic benefit of exploration program as well as to find an optimal time to stop exploration and start development. This tool was build based of VOI (value of information) approach which calculate economic benefit of geological information. One of the first pieces of research about value of information was [Howard, 1966]. In this paper VOI was defined as the difference between expect value of target function when the information is available and when it is not. Net VOI is equal to VOI minus cost of obtaining the information. VOI approach has been used successfully for a long time in oil industry. One example is [Barros et al, 2015] paper. VOI was calculated to improve wells management. Authors found optimal time to obtain information before making field development decision. There is a good overview of VOI application in oil industry in [Bratvold et al, 2009]. In this paper we used VOI approach to optimize exploration program for an Eastern Siberia oil field. We built VOI maps showing economic benefit of building exploration well in each possible location. The benefit is calculated based on stochastic geological model. This approach is designed for finding best exploration wells location and for finding optimal number of exploration wells.

Paper present a case study of successful implementation of integrated well-testing and production logging in a complex carbonate reservoir during exploration and production. Reservoir model was tuned to match well-testing and production logging. Due to that actual production data shown pretty good match with preliminary made production forecast. Integrated well-testing and production logging give information to improve development scheme and optimize acid treatment. Additional well-testing program of producers is prepared to decrease shut-in time without decrease well-test quality.

The paper presents the approach to monitoring, analysis and management efficiency of oil fields development – proactive block analysis. Powered methodological substantiation implemented as a software module algorithms, scope and results of test calculations.

The paper describes a scientific and methodical approach to the restoration of reservoir oil composition and pVT-properties according to data on the composition of dissolved gas and the gas factor on the stages of the field separation system and the density of the stock tank oil. Based on the identified composition of the reservoir oil, the PVT-model that adequately reproduces the results of laboratory and field studies is created. The composition of the free gas cap is identified as a result of vapor/liquid equilibrium mathematical simulation using equation of state. The created pVT-models of formation oil and gas condensate mixture can be used in the design and monitoring of reservoir development using modern hydrodynamic simulators based on Black Oil or/and compositional approach. The application of the suggested method is illustrated for the real deposit.

The article discusses about the use of probabilistic approach to estimate the costs of surface facilities in the early stages of investment projects estimation, starting from the accepted prerequisites for creation probabilistic models for main types of surface facilities, determination of the variability intervals to evaluation of the impact on economic evaluation of the project at the end. The paper describes the main shortcomings of the common deterministic (scenario-based) approach to estimate the costs of surface facilities and the benefits of probabilistic cost estimating. Construction of probability distributions is based on statistically data of the actual surface facilities costs of the company, structured by types, diameters, regions, and other characteristics. The main drivers of changes in value and uncertainty of different types of surface facilities are analyzed. On the basis of probability distributions by types of construction objects with the use of specialized software the final distribution of costs for surface facilities of the asset, allowing to estimate the range of changes in value with a given probability is calculated. For example, the results of the analysis show that the implementation of pessimistic or close-to-it scenario of surface facilities cost can often lead to a significant reduction in the effectiveness of the project. In the early stages of project evaluation, when there are no field data, project documentation, in other words only very limited set of project information is available, the proposed methodology allows to evaluate and justify the interval of possible variation of the investment volume with a given probability. Using the proposed approach allows us to more fully appreciate the risks on the underlying assets, and increase the flexibility of investment decisions.