=Paper=
{{Paper
|id=Vol-2485/paper37
|storemode=property
|title=Improving the Accuracy of Hydrocarbon Reserves Estimation Based on an Integrated Approach
|pdfUrl=https://ceur-ws.org/Vol-2485/paper37.pdf
|volume=Vol-2485
|authors=Dmitry Zavyalov
}}
==Improving the Accuracy of Hydrocarbon Reserves Estimation Based on an Integrated Approach==
https://ceur-ws.org/Vol-2485/paper37.pdf
Improving the Accuracy of Hydrocarbon Reserves Estimation Based on
an Integrated Approach
D.A. Zavyalov1
zda@tpu.ru
1
Tomsk Polytechnic University, Tomsk, Russia
The paper presents an integrated approach to computer modeling of hydrocarbon deposits, as well as the results of its application
in oil volume calculation. Such approach involves all available information, as well as visual analytics, and allows to get a more accurate
and reliable distribution of parameters in the volume of the three-dimensional computer model of hydrocarbon deposit due to its
adjustment based on actual (historical) information about the operation of the oil field. The adjusted in this way model allows to obtain
a more accurate predictive solution for the development and to improve the management efficiency of hydrocarbon deposits.
Keywords: oil and gas field, oil field managing, oil volume calculation, integrated approach, visual analytics.
To assess the reliability of oil reserves estimation on the
1. Introduction basis of the integrated model, one of the fields of Tomsk
Region the designing history of which includes more than one
The hydrocarbon field is a large socio-economic system
reserves calculation project was selected. There are geological
(SES) that has a complex hierarchical structure and is closely
models and protocols about approved oil reserves on their
interconnected with other SES (administratively, basis, as well as data on drilled production wells and
infrastructurally, economically), and sometimes determines
retrospective information (historical data) on their operation
their progress. The hydrocarbon field includes both
regimes (table 1).
underground oil deposits and ground-based infrastructure
(pipelines, power plants, residential and working premises, Table 1. Projects on development of hydrocarbon fields
roads, etc.), as well as drilled wells (oil-production, injection,
by years
water-production, and others). Usually three organizational
Hydrocarbon
systems participate in managing a field at different stages: the Development Model
reserves
state, a subsoil user company, and a project institute, which project adjustment
estimation
include specialists of different profiles, whose interaction is
often inconsistent.
2006 ✔
Considering the volume of capital investments (the cost of 2007 ✔
drilling and developing wells, conducting research and field 2008 ✔ ✔
works) and the operating costs of developing the fields, as well 2009 ✔
as the degree of uncertainty in carrying out the works, the 2010
planning task becomes critical in managing the field as a socio- 2011 ✔ ✔
economic system. This problem is solved with the development
designing process, the result of which is a long-term strategy 2012 ✔
for the functioning of the field. 2013
The basis of any field development project is detailed three- 2014 ✔
dimensional computer model, the accuracy and reliability of 2015
which determine the feasibility of the development strategy, 2016 ✔
and therefore the management efficiency of the SES
"hydrocarbon field" [1]. The first hydrocarbon reserves estimation at the field was
carried out in 2006, the subsequent ones were in 2008 and 2011.
2. Three-dimensional computer models of Industrial development of the field has been conducted from
hydrocarbon fields 2008 to the present (data are available till 2016).
The field model is a three-dimensional digital interpretation As an illustration of changes in ideas about the geological
of the real formation according to a number of parameters structure of the field, fig. 1 shows the structural maps of the top
(porosity, permeability, oil saturation, etc.), and the modeling of the reservoir in different years of calculating reserves, which
process itself is the restoration of those parameters from several were approved at the state level. Fig. 2 presents the history of
observation points (studies in drilled wells). Obviously, in the the designing of this field based on available project and
early stages of deposits lifecycle, the reliability of geological historical data.
models is lower due to the smaller number of such observation The volume of oil reserves approved in 2006 at the field
points. However, the reliability of the models is determined not was 5,825 thousand tons. This calculation was carried out on
only by the density of the grid of observations or the quality of the eastern part of the reservoir, in which an inflow of oil from
research, but also by the complexity and heterogeneity of the a drilled well was obtained.
geological structure of the field. To increase the reliability of In 2007, on the basis of the first oil reserves calculation, the
field models, an integrated approach to modeling is required, first project document for the field was developed, according to
which means the involving of all available information, as well which its commercial operation began in 2008. The oil inflows
as visualization tools and visual analytics. got in 3 drilled wells gave reason to carry out a new calculation
of oil reserves in 2008 and to put the remaining oil deposits on
3. An integrated model of hydrocarbon field the balance of the subsoil user (the volume of reserves
increased to 17,744 thousand tons) – the reservoir area has
In this paper, the effectiveness of the use of an integrated increased according to the modelling results.
field model by the effect on the reliability (in terms of accuracy
of estimating oil reserves) of the geological model and reserves
estimation is assessed.
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Based on the second reserves calculation, in 2009 a new
project document was developed for the operation of the field,
which involved intensive drilling of the reservoir – 19 new
wells were drilled, some of which did not confirm the oil
content of part of the reservoir. Thus in 2011, the third
calculation of reserves was carried out, which reduced the area
of the deposit and the reserves - their volume decreased to
15,973 thousand tons of oil.
Fig. 2 shows a comparison of designed and historical
indicators of annual oil production in the field. Throughout the
а) entire period of the field’s operation, the actual volumes of oil
production lag behind the designed ones.
Each project document for the development of a field
implies an analysis of its development history. Among the
reasons for the failure to achieve the approved project
indicators, in addition to high expectations and the erroneous
idea of the geological structure of the field, experts in the
reports indicate a higher actual water cut than in the project,
which along with relative phase permeabilities is determined
by the property of initial water saturation in the field model.
b) Thus, in this case, we can speak of an overestimated value of
the initial oil saturation in the field model.
For putting on the state balance, oil reserves are estimated
as the sum of the oil volume of all cells of the effective oil-
saturated part of the 3D-geological model (fig. 3). The
volumetric method is the following:
𝑉𝑜 = 𝜌𝑜 ∗ 𝐵𝑜 ∗ ∑𝑛𝑖=1(𝑉𝑏𝑖 ∗ 𝑃𝑜𝑟𝑜𝑖 ∗ 𝑆𝑜𝑖 ), (1)
where Vo is the volume of oil reserves; i, n – respectively, the
index and the number of cells in the model; Vbi – the rock
volume, Poroi – the porosity coefficient, Soi – the oil saturation
coefficient of the i-th cell of the model; ρo – the oil density; Bo
c) – the volumetric coefficient of oil [2, 3].
Fig. 1. Change of ideas about the geological structure
of the field in time: a) 2006, b) 2008, c) 2011
Fig. 2. The history of the designing and production of oil in the field
(VE – reserves volume estimation, DP – development project)
а)
Fig. 3. 3D geological model of the field
Moreover, in a two-phase system (oil-water), the sum of
saturations is equal to one, therefore, So in each cell of the model
is calculated by the formula:
1
−
𝐵
3,183∗(𝜌𝑤− 𝜌𝑜)∗𝑔∗ℎ 𝑃𝑒𝑟𝑚
𝑆𝑜 = 1 − ( ∗ √ ) , (2) b)
𝐴∗ 𝛾∗cos(𝜃) 𝑃𝑜𝑟𝑜
Fig. 4. Oil production in wells: a) history, b) model
where ρw is the density of water, ρo – the density of oil, g – the
acceleration of gravity, h – the height relative to the level of free An integrated approach to geological modeling made it
water, γ – the surface tension between oil and water, θ – the possible to obtain a more correct distribution of permeability (fig.
wettability angle, A and B are the coefficients of the power 5), initial oil saturation (fig. 6) and initial oil reserves over the
dependence of the Leverett J-function, which has the form: area and volume of the oilfield model, which makes it possible
𝐽(𝑆𝑤) = 𝐴 ∗ 𝑆𝑤 −𝐵 , (3) to obtain a more correct forecast decision and make more
where coefficients A and B are calculated on the basis of the adequate field development strategy. The recalculated
results of laboratory core tests. parameters turned out to be closer in value to the parameters
In geological modeling, the calculation of permeability in obtained in the 2011 project, when 12% of oil reserves were
models is based on the results of geophysical studies in wells as written off.
a function of porosity. Darcy's law allows to solve the inverse
problem of calculating the permeability value in the well area:
𝑟𝑒
18.41∗ 𝜇𝑜 ∗ 𝐵𝑜 ∗(ln( )−0.75+𝑆)
𝑟𝑤
𝐾 = 𝑞𝑜 ∗ , (4)
ℎ∗(𝑃̅𝑟− 𝑃𝑤𝑓)
where qo is the oil production rate (m3/day), K – the permeability
(mD), h – the effective reservoir thickness (m), Pr – the average
reservoir pressure (atm), Pwf – the bottomhole pressure of the
well (atm), μo – the oil viscosity in reservoir conditions (cP), Bo
– oil volumetric coefficient (m3/m3), re – drainage radius (m), rw
– well radius (m), S – skin factor.
In the designing of hydrocarbon field development, thematic
mapping is widely used for operational monitoring of а)
development, visual analysis of the history and development
status, prediction of reservoir behavior and so on. In addition,
such tools as time series analysis, slices of multidimensional
data, sections of data cubes, geological and statistical sections
and others are widely used for visual analytics [4, 5, 6, 7, 8].
At the first step, to analyze the correspondence of the
parameters of the field model to the real reservoir, maps of the
distribution of the actual and model oil production were
constructed, which made it possible to conclude that the
geological model of the field was unreliable and there is the need
for its correction. Based on a comparison of production maps,
b)
areas of the model that require adjustment of parameters were
Fig. 5. Average maps of permeability: a) approved model, b)
identified (fig. 4).
adjusted
To correct permeability in the 2008 project model time series
characterizing the dynamics of actual production of wells were
The use of such an integrated approach to modeling a number
analyzed, after that, based on (4) new values of permeability in
of fields has let to increase the accuracy of estimating
wells were calculated. Interpolation of new values of
hydrocarbon reserves by 0.7 to 3.2%.
permeability in the volume of the reservoir model allows to
adjust the initial oil saturation according to (3), (2) and further
4. Conclusion
recalculating of the initial oil reserves by formula (1).
The average value of reservoir permeability decreased by The paper presents an integrated approach to estimating the
12.1% (from 6.79 mD to 5.97 mD), oil saturation decreased by volume of hydrocarbon reserves, which allows to increase the
1.4% (from 0.579 u.f. to 0.571 u.f.), which led to a reduction in accuracy of such an assessment and the reliability of the
the recalculated oil reserves by 0.9% compared with the standard geological model of the field. The model adjusted in this way
approach. allows to obtain a more accurate predictive solution for the
development and to improve the management efficiency of the
SES “hydrocarbon field”.
а)
b)
Fig. 6. Average maps of oil saturation: a) approved
model, b) adjusted model
5. Acknowledgements
This work has been supported by the Ministry of Education
and Science of the Russian Federation with the Grant No.
2.1642.2017/4.6.
6. References
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