Seismicity and development of Romashkino hydrocarbon field’s Almetyevskaya area

The relationship between the various human activities and seismic activity has become more evident in the last several decades. One of the important domains where such a relationship manifests itself is hydrocarbon fields’ development. South East Tatarstan (Russia) is a region where the link between seismicity and the development of the giant Romashkino hydrocarbon field has been established. The goal of the current study is to conduct the causative analysis between the seismic activity and the development of the Romashkino hydrocarbon field’s Almetyevskaya area which is located in the most seismically active zone of the south-eastern Tatarstan.

Hydrocarbon Field Re-Development in a Bayesian Framework

Hydrocarbon field (re-)development projects are challenging to perform as a number of decisions need to be taken under uncertainty. In addition, data gathering activities need to be performed to decrease the risk of negative outcomes related to project objectives and to select the development option with the highest value. Many oil and gas E&P companies are using as stage-gate process to mature hydrocarbon field (re-)development projects. Such a process allows for systematic project development including value assurance measures such as peer reviews prior to decision gates. However, the stage-gate leads to challenges if it is not performed in a Bayesian framework. If for example simplified models are used in the early phase of the stage-gate process, no Bayesian updating of believes can be done. Similarly, if the company is not seamlessly integrating project value in project development, the value of development option and of data acquisition cannot be quantitatively determined. We are showing how to mature projects in a Bayesian framework. We show how data gathering is used to update believes and how generalized sensitivity analysis can be applied to identify which decisions have an impact of project value and which parameters are sensitive to the decision which development option to perform. The key performance indicators such as Expected Monetary Value, Probability of Maturation, Probability of Economic Success are updated. The changes of the sensitivities of the various uncertain parameters with project maturation is monitored and the decision maker is supplied with key performance indicators and residual risks, risk mitigation and management plans at Final Investment Decision.

Hydrocarbon Field Re-Development as Markov Decision Process

Hydrocarbon field (re-)development requires that a multitude of decisions are made under uncertainty. These decisions include the type and size of surface facilities, location, configuration and number of wells but also which data to acquire. Both types of decisions, which development to choose and which data to acquire, are strongly coupled. The aim of appraisal is to maximize value while minimizing data acquisition costs. These decisions have to be done under uncertainty owing to the inherent uncertainty of the subsurface but also of other costs and economic parameters. Conventional Value Of Information (VOI) evaluations can be used to determine how much can be spend to acquire data. However, VOI is very challenging to calculate for complex sequences of decisions with various costs and including the risk attitude of the decision maker. We are using a fully observable Markov-Decision-Process (MDP) to determine the policy for the sequence and type of measurements and decisions to do. A fully observable MDP is characterised by the states (here: description of the system at a certain point in time), actions (here: measurements and development scenario), transition function (probabilities of transitioning from one state to the next), and rewards (costs for measurements, Expected Monetary Value (EMV) of development options). Solving the MDP gives the optimum policy, sequence of the decisions, the Probability Of Maturation (POM) of a project, the Expected Monetary Value (EMV), the expected loss, the expected appraisal costs, and the Probability of Economic Success (PES). These key performance indicators can then be used to select in a portfolio of projects the ones generating the highest expected reward for the company. Combining the production forecasts from numerical model ensembles with probabilistic capital and operating expenditures and economic parameters allows for quantitative decision making under uncertainty.

Prediction of Current Production Rates, Cumulative Production and Recoverable Reserves of Hydrocarbon Fields

Modeling in the process of oil production has been used almost since the beginning of hydrocarbon field development, when there were ideas about the conditions of formation occurrence and oil flow to wells. An empirical model is proposed to calculate the current production rate of wells in the hydrocarbon field by year. Based on this model, an equation for calculating cumulative production was constructed. The proposed model is compared with known models and actual development history data. The resulting models of current production rates, cumulative production and recoverable reserves most accurately describe the actual results and have a high correlation parameter compared to other models.

Geological and geophysical analysis of morphological structures of the central type in the Eastern European platform territory and its connection with hydrocarbon fields

Correlative interrelation of hydrocarbon field arrangement and morphological structures of the central type is revealed. Possible natural mechanisms of morphological structures formation of the central type are considered. By results of geological and geophysical interpretation of magnetic prospecting, gravity prospecting, heat floor data the deep structure of these morphological structures is shown.

Fracture modeling of carbonate reservoirs of Low Triassic Neftekumsk formation of hydrocarbon field in Petrel software

Construction of geologic and hydrodynamic models of carbonate reservoirs in the conditions of information lack about fracture parameters is always connected with the high degree of uncertainty. In the article the approach to the studying and the prediction of fracture of the carbonate reservoir based on the distribution and the trending of tectonic stress in the region of the researching object is presented. As illustrated by one of the field of the Eastern Caucasus the geotectonic description of the territory is listed, the fracture parameters on the indirect data were received, the zones of the increased productivity (fracturing) of reservoirs were highlighted and the modeling of fractures was held in Petrel software.

Hydrocarbon field development forecast based on an integrated approach

A hydrocarbon field is a large and complex system, which functioning is possible only in accordance with a project document that defines the main characteristics for the entire period of field development. Therefore, the quality of the project document largely determines the efficiency of the field system functioning. The last stage in creating a project document for the development of a field is an economic assessment. According to the experience of designing the development of hydrocarbon fields, up to 50% of capital investments are the costs of drilling new wells of various types. Thus, the economic efficiency of field development is largely determined by the volume of drilling new wells. The article presents an integrated approach to modeling the development of hydrocarbon deposits in making a production forecast. Such an integrated approach involves performing a rapid economic assessment using Economics software which allows you to calculate the main economic indicators of field development. Thus, it reduces the total number of iterations for setting the forecast for field development strategy by an average of 25% as well as improves the economic characteristics of the whole project.