=Paper=
{{Paper
|id=Vol-2763/CPT2020_paper_s7-4
|storemode=property
|title=Hydrocarbon field development forecast based on an integrated approach
|pdfUrl=https://ceur-ws.org/Vol-2763/CPT2020_paper_s7-4.pdf
|volume=Vol-2763
|authors=Zavyalov Dmitry Alekseevich
}}
==Hydrocarbon field development forecast based on an integrated approach==
https://ceur-ws.org/Vol-2763/CPT2020_paper_s7-4.pdf
Hydrocarbon field development forecast based on an integrated
approach
D.A. Zavyalov1, 2
zda@tpu.ru
1
Tomsk Polytechnic University, Tomsk, Russia
2
Keldysh Institute of Applied Mathematics RAS, Moscow, Russia
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.
Keywords: oil and gas field, oil field managing, integrated approach, economic estimation.
• hydrodynamic modeling (construction of a
1. Introduction hydrodynamic model of the field based on geological
The complexity of the structure of such a system as model);
hydrocarbon deposits, as well as the complexity of the • development forecast (calculation of several forecast
management processes of such a system, determine the variants for field development strategy based on a
importance of strategic planning. The development of hydrodynamic model);
hydrocarbon deposits is carried out in accordance with the • economic assessment of the forecast (calculation of
project document, which is a long-term field development economic indicators of forecast variants for field
strategy and states the number of drilling of new wells, development strategy).
volumes of hydrocarbon production, the need and volume
of construction of new infrastructure facilities (such as
pipelines, living and working spaces, power plants and
others) and new research (seismic, exploration drilling,
borehole surveys and more) volumes.
Therefore, the quality of the field development forecast
is the determining function of efficiency of the functioning
of such a complex system. The forecast is drawn up for the
entire period of field development and must take into
account the influence and interaction of all components of
the hydrocarbon field system, as well as adjacent systems.
However, the existing approaches to managing field
development have a number of significant drawbacks:
disunity of specialists, multivariance and iterativeness of
designing stages, dependence of the result of each stage on
the quality of previous ones.
So, to increase the efficiency of hydrocarbon field
development management, an integrated approach to the
process of formation of a development strategy is required.
2. Integrated approach to modeling the
development of hydrocarbon deposits
In general, the process of project management of
hydrocarbon field development is a sequence of stages
presented on Fig. 1. This process involves the sequential
execution of the following stages: Fig. 1. Stages of the project management process for
• processing of initial data (including data verification hydrocarbon field development
and formatting);
• geological modeling of the field (construction of a The result of presented sequence of stages is a project
geological static model for assessing the structure of document for the development of the field.
the field and calculating the volume of hydrocarbon The main types of projects are the calculation of
reserves); hydrocarbon reserves (assumes the implementation of
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY
4.0)
stages S1-S2) and the forecast of field development If we talk about economic factors which the most
(assumes the implementation of the entire chain of stages strongly influence on the development of the field,
S1-S6). external macroeconomic indicators should also be
Stages S2, S4, S5 are variable (require a lot of variants distinguished, however, they are difficult to predict and
for decision making) and iterative (each variant is cannot be changed. Such indicators must be incorporated
calculated many times till the satisfactory result is into the project to reduce uncertainties [4, 5].
obtained), and unsatisfactory results of stages S3, S5 may
require returning to the previous stages (arrows (1) and (2)
on Figure 1) in order to correct some options or completely
change the approach to development design.
The most time-consuming is stage S4 - development
forecast, the result of which becomes a long-term strategy
for the functioning of the field. When performing this
stage, iterative modeling of a number of field development
forecast variants (the number of variants depends on the
complexity of the structure of the field and can be several
dozen) is used [1, 2].
For example, at one of the fields in the Tomsk Region
there are 4 reservoirs by different in properties, for each of
which 3 variants are first calculated to select the system
for placing project wells, and then for the selected
placement system for each reservoir 4 more variants are
calculated to select the optimal operating modes for Fig. 3. An example of the structure of total capital investments
project wells. Thus, the total number of variants is 28, in the development of an oil field
while the average number of tuning iterations of one
variant is 10. The time of one iteration includes the time of The cost of extracting one ton of raw material is
calculating the model and setting its parameters and varies characterized by such an indicator as a ton of unit fuel. The
from several hours to a week depending on the complexity value of this indicator at the end of the development period
and dimension of the model, the number of phases and as production levels fall, increases (see Figure 4). Thus,
other parameters. All this determines the laboriousness of the maintenance of a low-rate well becomes unprofitable.
obtaining a field development forecast. However, an incorrect determination of the location of the
As experience in the implementation of hydrocarbon well drilling may lead to the fact that the low oil
field development projects shows, economic profitability production rate obtained in it will not allow to recoup the
is largely determined by the volume of well drilling, since cost of its drilling. Therefore, it is necessary to exclude
up to 50% of the capital investment is in drilling the obviously ineffective (from an economic point of view)
production and injection wells. wells from the forecast variants for the development of the
Figs. 2 and 3 show the example structure of capital field in order to increase the overall cost-effectiveness of
investments in the development of one of the real deposits the development variant.
in the Tomsk region [3]. In this example, the project costs
for drilling new wells in 2021-2025 (during this period, the
main part of the forecast wells was drilled) ranged from
30% to 80% of the amount of capital investments (Figure
2), while the total costs for the entire period reached 44%
(Figure 3) of the total amount of capital investments to
field development.
Fig. 4. An example of a graph of average costs per ton of unit
fuel
To reduce the interactiveness of predictive modeling,
it is necessary to consider economic parameters at the
stage of formation of development variants:
• accounting of capital investments: drilling wells
(calculation of penetration depth depending on the
Fig. 2. An example of the structure of capital investments in the
development of an oil field by years type of well), tacking (number of bushes and
machines used simultaneously), arrangement of in the produced fluid to shutdown both individual
infrastructure (necessary and available capacities); production wells and the entire field), minimum well
• operating costs: development time, production and production, production compensation, etc. This variant
injection levels. may not have economic profitability, which is
Accounting of capital investments in the development disadvantageous for the subsoil user. Also, restrictions are
project along with unit hydrocarbon production at the well imposed by the models themselves or the simulators used.
placement stage allows us to evaluate the feasibility of It is proposed to supplement the algorithm for
drilling exact wells. predictive modeling of field development with a new unit
The main criteria for choosing a forecast well for performing a rapid economic assessment S'5 of the
placement system can be divided into several groups. The results of calculation iteration (see Fig. 5). Thus, advanced
selection criteria for the well placement system (in-line, production forecast stage S'4 can be represented as:
three-point, five-point, nine-point, selective) are usually S'4 = S4 ∪ S'5, (1)
determined by the existing experience in developing this
where
type of reservoir and the proven placement system is used.
Different well placement systems are characterized by a S'5 ⸦ S5. (2)
different ratio of production and injection wells (which is
important for maintaining reservoir pressure), some of the
systems have the possibility of transformability (one
system can be transformed into another by changing the
type of some of the wells or by drilling extra ones). To
select the optimal distance between the wells in the
system, several variants are calculated [6].
The main criteria for selecting locations for new
production wells include:
• distance from the oil-water contact (conditional
surface separating oil and water in the oil reservoir
and determining the ratio of water and oil in the
fluid produced by wells at the field);
• effective oil-saturated thickness (reservoir power
determines the volume of hydrocarbons in the
reservoir and as a consequence well production
rate).
It should be considered that the grid of wells should be
regular and correspond to one of the existing systems of
well arrangements. However, in some cases it is necessary
to use selective well placement systems (high density of
existing wells, non-standard form of the reservoir or its
small area).
The choice of the type of well (directional, horizontal
or sidetrack) is based on the geological and geophysical
conditions of the formation. For example, with high
ruggedness it is not practical to drill horizontal wells, but
the coverage of such wells is higher than directional wells Fig. 5. Advanced algorithm for predictive modeling of field
which makes it possible to obtain a higher oil production development
rate during well operation and, therefore, to reduce the cost
of extracting each ton of liquid, also horizontal wells At the same time, adding an additional block to the
increase the density of the well grid. algorithm does not significantly affect the iteration
To form an effective development management execution time, but it allows significantly reduce the total
strategy for predictive modeling, development options are number of iterations when setting up the S'4 development
configured in accordance with the criteria, some of which forecast by introducing additional restrictions on the
are regulated (mandatory) on the state level [6, 7], the placement of forecast production wells: setting boundary
others are set by the subsoil user or dictated by the conditions by involving the economic component of the
operating conditions of the field, as well as its parameters. project.
For example, it must be considered that many fields are The proposed algorithm uses GDM-Tool software
characterized by severe climatic conditions, which (certificate of state registration of a computer program №
imposes a number of restrictions on the intensity of drilling 2011616248 «GDM-Tool») for well placement S41
of new wells due to the seasonality of work. The variant (depending on the location of the oil-water contact contour
recommended for approval must meet the requirements of and the distribution of oil-saturated thicknesses), setting
regulatory documents (established by the government): drilling and operating schedules, as well as operating
achieving an approved oil recovery factor (the proportion modes S42 of project wells.
of hydrocarbon reserves that are technically possible to
extract), water cut of 98% (the percentage of water content
The first iteration of product forecast calculation Tomsk region, completed in different years, was used. The
allows you to get estimated indicators of production levels deposits are distinguished by the complexity of their
(starting production and cumulative production of each geological structure, different depths of occurrence of
well) and calculate estimated economic indicators. Based productive strata, properties of fluids, degree of
on the obtained data, the forecasted fund of production exploration and development. Each dataset includes both
wells is optimized by eliminating inefficient or obviously the complete initial datasets for building models and
unprofitable ones, thereby reducing the number of forecasting development, as well as geological and
iterations when setting up a development variant further. simulation models and forecasts that have passed
Software Economics (certificate of state registration of government expertise and have been approved as field
a computer program № 2019611730 «Economic rapid development strategies.
assessment of the results of predictive modeling of the The forecast variants for hydrocarbon field
development of oil and gas fields (Economics)») is used to development were tuned until acceptable indicators were
perform rapid economic assessment S'5. It allows you to achieved according to the existing algorithm and
calculate the main economic indicators of development, as according to the improved algorithm with the new block
well as to calculate the minimum cost-effective production of rapid economic assessment. Evaluation of the
rate of forecast wells and the minimum cost-effective effectiveness of the proposed approach was carried out by
effective oil-saturated thickness for placing wells for a counting the number of iterations of the calculation of one
given field. Thus, it becomes possible to perform forecast variant for development strategy of hydrocarbon
adjustment of the prediction well arrangement to reduce field.
the interactiveness of the predictive modeling process. The results are shown in Table 1. For various sets of
test data (field development projects), the average number
3. Results of iterations for setting up production forecast variants for
To assess the effectiveness of the proposed integrated field development was reduced by 15.8% to 35.6%.
approach, data on 9 field development projects in the
Table 1. Average number of iterations for setting the forecast for field development
The average number of iterations, pcs.
Data set Existing project Advanced project management The effect, %
management algorithm algorithm
1 7,1 4,8 32,4
2 7,8 6,0 23,1
3 6,3 4,8 23,8
4 5,7 4,8 15,8
5 10,2 7,2 29,4
6 9,5 7,2 24,2
7 5,8 4,8 17,2
8 9,3 7,2 22,6
9 14,9 9,6 35,6
Due to the use of the advanced algorithm with rapid 4. Conclusion
economic assessment, the average number of iterations to Thus, the use of the rapid economic assessment of
configurate one forecast variant was reduced by 25% (see hydrocarbon field development forecast variants based on
Fig. 6), which allows us to quickly and with less labor to an integrated approach made it possible to advance the
obtain a design solution for developing a field. existing forecast modeling algorithm and reduce the
number of iterations for adjusting the development
forecast variant by an average of 25%.
In addition, taking into account the large number of
field development forecast variants (which, as in the above
example, can reach several tens) considered in the
designing process in absolute terms, the reduction in
decision-making time in field management is significant.
Moreover, the application of this approach has made it
possible to significantly reduce the total volume of capital
investments (most of which are precisely the costs of
drilling new wells of different types) in field development
projects by optimizing the design well stock and thus to
improve the economic characteristics of the whole
hydrocarbon field development project.
Fig. 6. The number of iterations to configure one forecast
variant
Acknowledgments
The reported study was funded by RFBR, project
number 18-41-700001.
References
[1] Skorobogatov, V.A. Research and Development of
the Hydrocarbons Potential of the Soils of the Western
Siberian Sedimentary Megabasin: Results and
Perspectives // Vesti Gazov. Nauk. Mosc.: Gazprom
VNIIGAZ LLC. – 2014 (3). – P. 8–26.
[2] Pakyuz-Charrier E., Giraud J., Ogarko V., Lindsay
M., Jessell M. Drillhole uncertainty propagation for
three-dimensional geological modeling using Monte
Carlo // Tectonophysics. – 2018. – №747-748. – P.
16-39.
[3] Neftegazovaya otrasl Rossii. Available online:
http://fb.ru/article/263751/neftegazovaya–otrasl–
rossii (accessed on 17 July 2020).
[4] Zavyalov D.A. Improving the accuracy of
hydrocarbon reserves estimation based on an
integrated approach // CEUR Workshop Proceedings
of the 29th International Conference on Computer
Graphics and Vision (GraphiCon 2019). – Vol. 2485.
– P. 164-167. DOI: 10.30987/graphicon-2019-2-164-
167.
[5] Yang Y., Zhang M., Bie A., Cui Z., Xia Z. An
integrated approach to uncertainty assessment for
coalbed methane model // Springer Series in
Geomechanics and Geoengineering. – 2019. – P.
1560-1567.
[6] Ministry of Natural Resources of Russia. Guidelines
for the preparation of technical projects for the
development of hydrocarbon deposits. Available
online: http://www.gkz‐
rf.ru/sites/default/files/docs/metodicheskie_rekomen
dacii_po_pravilam_prektirovaniya_uvs.pdf (accessed
on 17 July 2020).
[7] Ministry of Natural Resources of Russia. Guidelines
for the application of the classification of reserves and
resources of oil and combustible gases. Available
online: http://www.gkz‐
rf.ru/sites/default/files/docs/metodicheskie_rekomen
dacii_po_primeneniyu_nkz_utverzhdennye.pdf
(accessed on 17 July 2020).
About the authors
Zavyalov Dmitry A., Tomsk Polytechnic University
(Tomsk), Keldysh Institute of Applied Mathematics RAS
(Moscow). E-mail: zda@tpu.ru.