Estimate of Radial Drilling Technology Efficiency for the Bashkir Operational Oilfields Objects of Perm Krai

Galkin, Sergey; Kochnev, Alexander; Зотиков, В И

doi:10.31897/pmi.2019.4.410

Cited by 10 publications

(7 citation statements)

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“…Presently, the following techniques are mainly used to forecast the IOR effects: forecast based on geological and field analysis, statistical analysis, machine-learning methods and reservoir simulation [47][48][49].…”

Section: Materials Methods and Backgroundmentioning

confidence: 99%

“…To forecast the effectiveness of the technology, a database of geological and process parameters has been created. For neural networks training, the parameters that influence the RJD technology effectiveness the most have been selected, as described in the articles [47,48] A total of 590 radial drilling operations have been carried out at 43 oil fields in Perm Krai. Geophysical survey results and performance data are available for all the wells, while well test results have been obtained for 259 wells only.…”

Section: Materials Methods and Backgroundmentioning

confidence: 99%

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The Application of Neural Networks to Forecast Radial Jet Drilling Effectiveness

2022

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This paper aims to study the applicability of machine-learning algorithms, specifically neural networks, for forecasting the effectiveness of Improved recovery methods. Radial jet drilling is the case operation in this study. Understanding changes in reservoir flow properties and their effect on liquid flow rate is essential to evaluate the radial jet drilling effectiveness. Therefore, liquid flow rate after radial jet drilling is the target variable, while geological and process parameters have been taken as features. The effect of various network parameters on learning quality has been assessed. As a result, conclusions on the applicability of neural networks to evaluate the radial jet drilling potential of wells in various geological conditions of carbonate reservoirs have been made.

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Section: Materials Methods and Backgroundmentioning

confidence: 99%

Section: Materials Methods and Backgroundmentioning

confidence: 99%

The Application of Neural Networks to Forecast Radial Jet Drilling Effectiveness

2022

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“…At the same time, intensive oil shows up to commercial inflows with high flow rates were obtained from domanikites in a number of wells. Established has been a trend in location of hydrocarbon deposits of Upper Devonian-Tournaisian carbonate sequence with a density of tectonic lineaments, indicating that the maximum fracturing zones development is most likely in the highest tectonic stress areas [6].…”

Section: Methodsmentioning

confidence: 99%

Oil Potential Prospects of Domanik sediments in the North-East of the Volga-Urals

Krivoshchekov

2022

IOP Conf. Ser.: Earth Environ. Sci.

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Due to the depletion of available mineral and raw material resources of conventional sediments there is a need to search for new promising areas of oil and gas exploration in Perm Krai. This article addresses Domanik sediments as a new source of hydrocarbons. Stratigraphically, these sediments belong to the Sargayev, Domanik and Mendym horizons and lithologically they are mainly represented by tight carbonate sediments and shales. These sediments are the main oil-source strata in the Volga-Ural province. The paper analyses the geological structure and distribution of these sediments in the study area. Thereupon, exploration recommendations have been formulated for the next few years. These mainly include subject-matter research, core sampling in the Domanik Formation sediments, special studies of reservoir properties, reactivation and study of discovered oil deposits in the Domanik strata. The main activities should be concentrated in the south and south-west of Perm Krai: in the area of the Bashkir Arch, in the south of the Upper-Kama Depression. The Solikamsk Depression is also of interest in this respect.

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“…At the same time, deposits of the Vereisk formation are characterized by the layering of clay and carbonate rocks, low total reservoir thicknesses (3-6 m). Low well flow rates when using standard technologies of hydrochloric acid treatment [1][2][3] and radial opening of the reservoir [4,5] are the reasons for relatively low oil production volumes, which makes the development of these deposits unprofitable. Most of the wells that have uncovered these deposits exploit only the lower more productive oil layers.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Crack Development Associated with Proppant Hydraulic Fracturing in a Clay-Carbonate Oil Deposit

Galkin¹,

Savitckii²,

Shustov³

et al. 2023

Fluid Dynamics &Amp; Materials Processing

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Survey and novel research data are used in the present study to classify/identify the lithological type of Verey age reservoirs' rocks. It is shown how the use of X-ray tomography can clarify the degree of heterogeneity, porosity and permeability of these rocks. These data are then used to elaborate a model of hydraulic fracturing. The resulting software can take into account the properties of proppant and breakdown fluid, thermal reservoir conditions, oil properties, well design data and even the filtration and elastic-mechanical properties of the rocks. Calculations of hydraulic fracturing crack formation are carried out and the results are compared with the data on hydraulic fracturing crack at standard conditions. Significant differences in crack formation in standard and lithotype models are determined. It is shown that the average width of the crack development for the lithotype model is 2.3 times higher than that for the standard model. Moreover, the coverage of crack development in height for the lithotype model is almost 2 times less than that for the standard model. The estimated fracture half-length for the lithotype model is 13.3% less than that of for the standard model. A higher dimensionless fracture conductivity is also obtained for the lithotype model. It is concluded that the proposed approach can increase the reliability of hydraulic fracturing crack models.

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Estimate of Radial Drilling Technology Efficiency for the Bashkir Operational Oilfields Objects of Perm Krai

Cited by 10 publications

References 0 publications

The Application of Neural Networks to Forecast Radial Jet Drilling Effectiveness

The Application of Neural Networks to Forecast Radial Jet Drilling Effectiveness

Oil Potential Prospects of Domanik sediments in the North-East of the Volga-Urals

Modeling of Crack Development Associated with Proppant Hydraulic Fracturing in a Clay-Carbonate Oil Deposit

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