SPE 136248

Fracture-Based Strategies for Carbonate Reservoir Development Alfred Davletbaev, RN-UfaNIPIneft, Vitaly Baikov, RN-UfaNIPIneft, Thomas Doe, Golder Associates Inc., Olga Emchenko, RN-UfaNIPIneft, Aleksey Zainulin, RN-UfaNIPIneft, Andrey Igoshin, RN-UfaNIPIneft, Aleksey Fedorov, RN-Severnaya Neft

Copyright 2010, Society of Petroleum Engineers This paper was prepared for presentation at the 2010 SPE Russian Oil & Gas Technical Conference and Exhibition held in Moscow, Russia, 2628 October 2010. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.

Abstract Carbonate reservoirs present both opportunities and challenges, especially in rocks that contain multiple, heterogeneous porosities. This study addresses a large carbonate reservoir with complex porosity types including porous matrix, fractures, faults, and vuggy zones. A fracture-focused strategy considers how these porosities behave in oil production, and uses this understanding to improve reservoir productivity. The subject of this work is a major carbonate reservoir that was initially developed by conventional methods. These approaches emphasized matrix properties using petrophysically-interpreted wireline logs. The early stages of production, which did not include pressure maintenance, found anomalous behaviors that were inconsistent with a matrix-only reservoir. The existing petrophysical data, which are valid only for porous rock, could not address fracture-based hypotheses. A program of fracture studies supported a re-analysis of the production strategies in light of reservoirs observed behaviors. The fracture-focused strategy employed FMI image logs along with production logs (PLT surveys) and temperature surveys. These well-based tools identified the locations of flow and their associated geologic features, which are appeared to be mainly fractured and vuggy horizons. Coring activities validated the FMI interpretations. A reexamination of well tests using supported a single-porosity, fracture flow model. Pressure derivative interpretations using fracture-based conceptual models associated well performance with geologic features, including both the vuggy zones and faults. The fracture-focused characterization program has developed improved conceptual models of the reservoir to support evolving production approaches including well acidizing, and other. The paper provides examples of successful well operations performed after appropriate field research. Introduction The pay zones in field A are carbonate deposites. The bulk volume of the fields oil in place is contained in lower Devonic carbonate reservoir D1. The oil in place is characterized by a high gas/oil ratio ( tonmRs

39.128= ) and low viscosity ( smPa = 5.2 ). The field has a very heterogenous geological structure; the many faults compartmentalize the whole field into multiple blocks. The extracted core samples are characterized by intensive vug and fracture development. Some samples are shown on Fig. 1 including: a highly-vugged sample with micro-fractures; a sparse-vugged sample with micro-fracture channels; a porous sample with micro-fractures; a highly-fractured sample (with a micro-fracture network); a fractured sample with a macro-fracture; and a porous sample with a macro-fracture. This defines the foremost problem in reservoir development design as that of determining the contribution of fractures, vugs and pores to the total flow. Reservoir and External Boundary Modeling during Well Test Data Interpretation During the field development process, dynamic well tests were regularly conducted in both stationary and nonstationary flow regimes. Well tests conducted with a nonstationary flow (normally, specified by the pressure buildup curve, or Build-up, in a stopped producing well, and the pressure drop curve, or Fall-off, in an injection well) help diagnose the reservoir model, the formation boundary model, and the well completion model. Initially, only vertical producing and injection wells set with different oil output periods were drilled. Therefore, all data processing assumed a vertical well model with a wellbore effect and a wellbore vicinity contamination skin-factor.

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The reservoir is, however, heterogenous due to impermeable structure faults and an artificial gas cap that formed during initial natural-depletion development. Fig. 2 shows a number of such impermeable-fault reservoir models; the faults can be seen on the log-log pressure change plots as the corresponding characteristic log derivative curve incline [Bourdet D. 2003]. Geophysical investigations diagnose such pressure behavior in certain wells as cases of gas influx from upper completion intervals, which testifies to the formation of the artificial gas cap (Fig. 3). During well tests, a steady-pressure boundary effect can be observed as the pressure disturbance reaches the gas cap; this triggers pressure stabilization, which makes the pressure derivative become zero. Therefore, different models must be used to interpret the structural peculiarities of external reservoir boundaries. The boundary models for the present reservoir included an infinite-reservoir model, various combinations of models with impermeable faults, and a steady-pressure boundary. When selecting the reservoir model, it is necessary to account for the different rock types present in the reservoir (porous, fractured and vuggy rock), i.e. the reservoir is triple-porous. Models of triple-porosity reservoirs are analyzed, for example, in [Abdassah D. & Ershaghi I. 1985] and [Escobar F.H. et al. 2004]. Fig. 4 geometrically illustrates the problem of modeling a fractured reservoir with two matrices having different porosity and permeability properties (PPPs). Assuming one matrix as porous and the other as vuggy may be one alternative. Fig. 5 shows log derivative plots for pressure change curves in a well without the wellbore effect. The model was sized so that the investigation radius should not be greater than the distance from a well to the reservoir boundary. The images indicate that, assuming different PPPs of the two matrices, two transition zones have to be dealt with. The pressure change curves for well tests conducted on a triple-porosity reservoir block show the discharge of both matrices into the fracture network. It becomes obvious that the problem of well test interpretation is considerably aggravated by the complexity of the external boundary models and the presence of triple-porosity rock. Given the different reservoir boundary simulations, selecting a single-porosity reservoir model for well test interpretation would appear as the best choice, since in that case we would have a minimum number of independent parameters. Determining the Maximum Fractured/Vugged Intervals In order to identify which type of rock cavities (fractures, vugs or pores) contributes to the bulk of the flow, the well temperature log and flow metering data were compared with those of core investigations and electric imaging results. The flow intervals were matched with the intervals which the electric imaging log found characterized by intensive fracture/vug development (Fig. 6). It should be noted that the high secondary porosity indicated by electric imaging is due to the vugs, for vug porosity is on average 20 times greater than fracture porosity. The active intervals (Fig. 6) correspond to the maximum fractured core samples, while field tests suggest that the non-active intervals correspond to porous/vuggy cores with undeveloped fracture networks. It follows that reservoir influx is virtually zero in intervals with high secondary porosity values but without intensive fracture growth. The actual production of Well 11 is provided b 59% of the net sand pay shown by the well logs. A number of other wells produce from an even thinner pay zone. Considering that the high-secondary-porosity/high-fracturedness intervals match the inflow intervals, the well influx and intake profiles are rather exact in locating the fractured and fractured/vuggy zones in the wellbore zone. The unit flow intervals obtained from geophysical surveys were used to create a flow model and set the fracture permeability parameter. Besides, the estimated number of active beds was later used in well test interpretation to estimate permeability from the conductivity data obtained. Validating a Single-Porosity Model for Well Test Data Interpretion It has been mentioned above that the inflow intervals match those of highly developed fracturedness/vugginess, while intervals having only pores/vugs and lacking fractures contribute virtually zero flow. On this assumption, the above-described triple-porosity model can be reduced to a double-porosity one which was proposed by Warren and Root in [Warren J.E. & Root. P.J. 1963]. This can be done by integrating pores, non-connected vugs and micro-fracture families into a single matrix, while macro-fractured and vugged/fractured intervals are integrated into a single fracture network. Fig. 7 shows how vugs interconnected by fractures are integrated in this manner into one fracture network, while non-connected (sparse) vugs and pores constitute the matrix, i.e. do not conduct liquid but act as the source of influx into the fractures. Example 1: Build-up Test of the Producing Well The informational value of the analyses carried out can be demonstrated on the example of Well 1. The test was conducted as follows: a pressure gauge was lowered into the gusher to measure the continuous pressure change that took place during the wells operating mode switchover; on completion of the last operating mode, the flow rates are mapped in the ascending order on the pressure change curve. The raw data was processed in Kappa Eng. Saphir. Fig. 8 shows the corresponding pressure and log derivative curves in log-log coordinates. It is noteworthy that despite the apparently short pressure buildup (Well 1 completed after 3.5 hours), the radial flow zone was located quite confidently, which in its turn helped determine water permeability of the reservoir, as well as its foundation pressure and skin factor. The image (the shape of the diagnostic plot) indicates that this reservoir is of the single porosity type, in other words, there was no double porosity observed. There were no impermeable faults obsereved within the investigated radius either. Diagnostic plots were generated for all the pressure buildup/drop curves; these plots showed no apparent trans-pore flow from

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the matrix into the fracture system. In a number of wells the pressure curves were monitored for the duration of several days. The shape of the diagnostic plots suggests that the behavior of the reservoir is that of a single-porosity one. This may be accounted for by the small size of its compartments (or blocks). The compartments height averaged 0.64 m (according to the electric log), the minimum value being 0.23 m and the maximum being 1.50 m. Estimating the Duration of Interpore Flow Below is an analytical calculation of time corresponding to the middle of the transition period. 1. Estimating the specific surface factor . The equation for in a Warren-Root model is as follows (see, e.g., [T.D. Van Golf-Racht, 1982]):

2)2(2 Lnn += where L is the characteristic compartment dimension which is given by (given 3=n ):

)(3 cabcababcL ++= . Let ; then assuming : , . mba 100== m 6.0 mL 77.1= 297.18 = m2. The parameter which describes interpore flow in the dimensionless form (e.g., [Warren J.E. & Root. P.J. 1963.]; [Van Golf-Racht T.D. 1982]) is given by:

2wfm rkk =

where matrix permeability , fracture system permeability , and well diameter

: .

)1(101 215 mDmkm= )1000(101 212 mDmk f =

mrw 11.0= 4103 =3. The time point corresponding to the middle of the transition period is given, in its dimensionless form, by (see [Horne R.N. 1995]):

minDt

)1ln(min =Dt . Geological data estimate the volume capacity of the fracture system 12.0 , which gives . The dimension time point of the half-transition period is given by (e.g., [Earlougher R.C. 1977]; [Horne R.N. 1995]):

7.1108min Dt

ktrct Dwt min2= .

Then, having , sPa = 3103 Pact 1103 9 , 08.0= , mrw 11.0= , , we get )1000(101 212 mDmk f = st 10 . The estimated values of the half-transition period of matrix-to-fracture-system flow for different compartment heights are given in Table 1. Fig. 9 compares analytical pressure change curves for different matrix compartment heights with the measured curve. Thus, owing to the small dimensions of the reservoir compartments, the double porosity effect is observed during very short time intervals and is not detected on the plots due to the wellbore effect. It can be inferred that the radial flow zone on diagnostic plots corresponds to the time point when the quasi-stationary flow regime takes over to make the whole reservoir behave like a single-porosity one.

Estimating Fracture System Permeability This problem cannot be solved by traditional methods (i.e. by means of geophysical well surveys based on a petrophysical model). Since no petrophysical correlations can be traced from carbonate core investigations, any empirical petrophysical formulae hold good solely for the porous reservoir (for cores with no fractures or vugs). Thus, for instance, injectivity in Well 2 during well test interpretation amounted to 570 mD. Core samples collected from that well suggest a strikingly different permeability value below 5 mD in 99% of the samples. This result only confirms the mentioned conclusion that influx into a well is chiefly from the fracture system. It becomes evident that in order to estimate permeability of the fracture network, reservoir permeability estimates for nonstationary-flow well tests must be used. It has already been noted that early radial flow from the fracture system and the interpore flow period are downplayed by the wellbore influence. Fig. 10 shows the pressure change curve with all the Warren-Root inflow regimes distinguished [Bourdet D. 2003]. The radial flow regime diagnosed by the measured curves describes radial flow in the fracture system and the matrix. Considering that fracture system permeability is far greater than that of the matrix ( ), the permeability value estimated from the well test data was used to retrieve that of the fracture system during flow modeling. Reservoir permeability estimated from well test data is mainly affected by the degree of fracture network development and provides for quantifying the intensity (density) of fractures.

mf kk >>

Changes in Reservoir Rock Flow Properties The available well test data were used in a water permeability dynamics (reservoir productivity) study during reservoir pressure drop by natural depletion. Fig. 11 shows the changes in water permeability, reservoir and bottom-hole pressure, and total liquid flow across time for a number of wells. According to the available data, a short period of water permeability drop is initially observed, the curve gradually leveling out at a later stage. It is important that this short drop in reservoir water permeability occurs only with reservoir/bottom-hole pressures above the bubble-point, which rules out the possibility of changes in the physicochemical properties of the fluid (e.g. gas flashing or paraphine dropout in remote areas of the reservoir) affecting this behavior.

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Example 2 Build-up Test of Producing Well, Sensitivity Study The diagnostic plot and the semilog plot for Well 2 are shown on Fig. 12. The log-log derivative plot is shown for the

differentiation interval. The image shows some noise in the measured curve on the radial flow section, which affects the estimate reliability for water permeability. The latter is calculated by the incline of a rectilinear radial flow section mapped on the semilogarithmic scale (e.g. [Earlougher R.C. 1977; Horne R.N. 1995]):

05.0lnln 1 = ii tt

*mQBconstkh = Data measured from the radial flow section was used to estimate the slope in a 95% confidence interval:

[Horne R.N. 1995]. Fig. 13 shows water permeability dynamics as varying from the average value within the confidence interval (the sensitivity analysis was performed for the estimate error of the slope ). The image demonstrates maintenance of the downward tendency of water permeability. Apart from that, another sensitivity study was performed for the production rate estimate error only to show that the downward tendency of has again maintained.

*m***** mmmmm +

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Conlusions Inflow/intake intervals match those of intensive fracture/vug development. Permeability values obtained from well tests are much higher than those found by core surveys. Fractures constitute the bulk of the flow. Zones of high fracture density and zones with vugs interconnected by fractures are integrated into a single fracture network (system); while pores, non-fractured vuggy zones, and micro-fractures within porous media comprise the matrix. Fractures (incl. macro-fractures and fracture-connected vugs) are the main flow conductor. Well test permeabilities were used to configure the fracture system permeability parameter of the flow model. Field test results played the key role in configuring the fracture system and served as the basis for the flow model. Nomenclature

sR - , m3/m3, m3/ton.

- oil viscosity, mPs, P; fc - fracture system compressibility, 1/Pa, 1/atm;

1mc , - matrix compressibility, 1 and 2, respectively, 1/Pa, 1/; 2mcf - fracture system porosity;

1m , 2m - porosity of matrix 1 and 2, respectively; fk - fracture system permeability, m

2, mD;

1mk , - permeability of matrix 1 and 2, respectively, m2, mD; 2mk

H - total thikness in the block model; half-thinkness of Matrix 1 and 2, respectively, m; wr - wellbore radius, m;

2121

1w

f

m rkk

H= , 2121 1 w

f

m rkk

H= - interporosity flow parametrs of Matrix 1 and 2, respectively;

ffmm

ff

ccc

+= 111,

ffmm

ff

ccc

+= 222 - storage-capacity parameters of Matrix 1 and 2, respectively;

- parameter characteristic of the fissured block, 1/m2; n - number of mutually orthogonal fracture groups; L - dimension of matrix blocks, m; a, b, c length of the different perpendicular block sides, block height of matrix, m; P = pressure, Pa, atm;

iP - current reservoir pressure, Pa, atm;

0iP - initial reservoir pressure, Pa, atm;

wfP - bottom-hole pressure, Pa, atm; kh/ - transmissibility, m2m/(Pas), mDm/cP;

*m - slop of the linear section on the bottom-hole pressure/log time plot; B - formation volume factor (FVF), m3/m3; Q - well rate, m3/s, m3/day;

0f , - fracture system porosity and permeability with the initial reservoir pressure , m2, mD; 0fk 0iPk - permeability variation factor, 1/Pa, 1/atm; - pore compressibility factor, 1/Pa, 1/atm; oc - reservoir oil compressibility, 1/Pa, 1/atm.

References D. Bourdet. 2003. Well Test Interpretation Models. Doddy Abdassah, Iraj Ershaghi. 1985. Triple-Porosity Systems for Representing Naturally Fractured Reservoirs. SPE 13409.

SPE Formation Evaluation (April) 113-127. Freddy H. Escobar, Nestor F. Saavedra, Gerson D. Escorcia, John H. Polania. 2004. Pressure and Pressure Derivative Analysis

without Type-Curve Matching for Triple Porosity Reservoirs. Paper SPE 88556 presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition. Perth, Australia, 18-20 Oct.

J.E. Warren, P.J. Root. 1963. The Behavior of Naturally Fractured Reservoirs. SPEJ 3 (3): 245-255, SPE-426-PA. T.D. Van Golf-Racht. 1982. Fundmentals of Fractured Reservoir Engineering. ELSELVIER Scientific Publishing Company.

Amsterdam-Oxford-New York.

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Roland N. Horne. 1995. Modern well test analysis. Palo Alto, California (May) Robert C. Earlougher, Jr. 1977. Advances in Well Test Analysis. Society of Petroleum Engineers, Inc. Richardson, TX. Victor N. Nikolaevsky. 1996. Geomechanics and Fluidodynamics with Application to Reservoir Engineering. Kluwer

Academic Publisher. Dordecht-Boston-London. R.I. Nigmatulin. 1990. Dynamics of Multiphase Media. Vol.1, 2, Hemisphere, N.Y. Tables

Table1: Half-transition periods of matrix-to-fracture system flow for different compartment heights

Figures

Fig. 1: Core samples demonstrate complexity of rock cavities and channels and reservoir heterogeneity

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Fig. 2: Different impearmeable-boundary models

Fig 3: Constant pressure sections in zones affected by the gas cap (confirmed by field tests and numerical simulations)

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Fig. 4: Triple-porosity reservoir model geometry

Fig. 5: Analytical pressure Log-Log derivative curves for a triple-porosity model

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Fig. 6: Well logs, core data, and fracture/double porosity analysis results

Fig. 7: Simplifying scheme: Reducing a triple-porosity model to a double-porosity one

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Fig. 8: Log-Log plot of the build-up test of Well 1

Fig. 9: Sensitivity analysis of the influence of block height (c) on the duration of matrix-to-fracture system flow

Fig. 10: Pressure diagnostic plot for a double-porosity reservoir

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Fig. 11: Dynamic plots for reservoir transmissibility, reservoir & bottom-hole pressure, and liquid flow rate

Fig. 12: Semilog (left) and log-log (right) plots showing the range of estimate errors for the incline (m*) parameter

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Fig. 13: Well permeability (transmissibility) dynamics for Well 2 with the deviation range

Fig. 14: Fracture system permeability as a function of reservoir pressure

Fig. 15: Log-log PBC plots (Well 6 of 2005/08 and Well 7 of 2006/05) used to diagnose the constant pressure zone (gas cap)

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Fig. 16: Wellbore flow metering data used to target the flow and acidizing candidate intervals (left); production data testify

to an increased production rate after the acidizing operation (right)

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