The Importance of Integrated Reservoir Characterization in the Performance Optimization of Brown Fields with Complex and Diagenized Reservoirs

Transcription

1 REGIONAL ASSOCIATION OF OIL, GAS & BIOFUELS SECTOR COMPANIES IN LATIN AMERICA AND THE CARIBBEAN The Importance of Integrated Reservoir Characterization in the Performance Optimization of Brown Fields with Complex and Diagenized Reservoirs Silvina A. Valente Petrobras 86th ARPEL Experts Level Meeting (RANE) Management of Reservoirs October 6-7, 2014 Buenos Aires, Argentina

2 Dealing with Brown Fields Huge amount of information. Data from different years, different sets of logs, different service companies. Lost data. Multidisciplinary team members providing all kinds of information. (geophysicists, geologists, reservoir engineers, production engineers, drilling and completion engineers, etc). 2

3 Static Models Static model doesn t seem to be so static. While constructing a 3D geocelularmodel, a production field is constantly generating more and more data. New wells drilled, new pressure tests, new production data, need to feed the static model even while being constructed. This is why it is so important multidisciplinary teams are aware of the geocelularmodel construction, its importance on the optimization of the field performance and the importance every member of the team provides the correct and accurate data. 3

4 Constructing the Geocel Model It s critical to keep it as simple as possible. Complexity will come up anyway. First, we define if structure or stratigraphy control fluids mobility on our field. May be both. In case structure does, we ask the geophysicist how the structure and faults conform the architecture of our field. Then we get the faults model and structural maps for each horizon interpreted on seismic. This will conform the frame of our geocelmodel. 4

5 The Importance of the Structure It s very important to understand the structure of the field (compartments, faults orientation, mono or multi structures, critical for different fluid contacts). Knowledge of main fault trends will help orient the grid in order to represent de possible fluid movement within reservoirs. If faults are almost vertical, just represent them as vertical ones, keep it simple. Also, we may want to know how the structure was while the different reservoirs were deposited. It will help to understand the possible orientation and geometry of bodies. Inverted structures might mask old reliefs. 5

6 Where Characterization Starts Once we have our architectural framework, we want to know how heterogeneous our reservoirs are. To this purpose, we observe our rock deposits (core, plugs, outcrops in case we have the analogy). We define our sedimentary environment of deposition. We can have more than one at the same field (carbonates, siliciclastics, volcanics). 6

7 Defining Facies for the Model Our objective is to define faciesfor our reservoir and non-reservoir rocks, to determine petrophysic data for each one. We may need to describe and set the stratigraphy of the sequence so vertical and areal limits (geometries) of beds are very precisely understood. By observation of the cores, we define the faciesthat can be detected then in logs. Sometimes our data allows us to define rock types, afterwards we will need to assure that rock types can be identified and extrapolated from core wells to all wells of the field. Once we define, in our key wells, the faciesdescribed in cores, we can proceed with its extrapolation using different methods (neural networks, petrophysical software products, etc). 7

8 Heterogeneity By observing at our rock data, we can have the dimension of the heterogeneity of our reservoirs. This heterogeneity can vary not only vertically, but laterally, so it is very important to transmit this to the reservoir engineers. Heterogeneity is critical at the time of water or gas injection (or any EOR methods), hence the importance of having the geologist and the reservoir engineer working together at this stage. Type of diagenesisis also key for the fluids movement within the reservoir, that s why it is critical that all processes as compactation, dissolution, dolomitization, cementation, etc. are very well understood by all members of the team. 8

9 Petrophysical Model For our geocelularmodel we need that each cell has its own facies, porosity, permeability, fluid saturation, capillary pressure, wettability. To this purpose, we create from core data, cross plots with laws that represent each petrophysicalproperty for every facies. Phi, K Swi Pc 9

10 Probabilities on Petrophysical Data Some of the faciesmay have more than one law, given their own heterogeneity. In case we can use Rock Types we do so, otherwise we create optimistic, average and pessimistic cases. The engineer that runs the simulation of the model, will have 3 cases to test the behavior of the production history (of each well as well as the whole field, or group of wells). opt avg pes avg opt pes avg opt pes 10

11 Uncertainty While modeling we are dealing with Uncertainty. Many times it is necessary to go back and forth from the simulation to the geocelularmodel to test different laws for properties in order to get the match that keeps the engineer and rest of the team comfortable. Given the uncertainty of the geocelmodel, sometimes it is necessary to use one of the n runs made for any of the petrophysicalproperties, instead of the average of it, if this approximates better the simulated production to the real production. 11

12 Fluids Distribution It is quite important to define fluid contacts within the field. Given data is so many, it is possible to make a good use of it: o well test data o logs o production behavior 12

13 Fluids Distribution in Compartmentalized Reservoirs Integrationof data givesusa betteridea of gas, oiland waterdistributionwithin each of our reservoirs.

14 Refining Water Saturation of the Model Once we have defined one or more fluid contacts by the said data, it is possible to refine it by use of the Capillary Pressure curves that we obtain from SCAL data (Special Core Analysis). As we have defined faciesfrom core observation, now we have Pc for the different facies. With this, we determine distance to OWC for each facies, using Leverett functions (J). Then we compare Swfrom logs vs. Swfrom J function, and we can use both Swcubes for simulation 14

15 Simulation Stage& Development Scenarios Once the team feels comfortable with the selected geo model that represents the field (or part of the field), many tasks can be developed: - Volumetric calculations to adjust OOIP, OGIP - Simulations of different pilots for: drilling change of pattern design conversions closing of zones perforations fracture or refracture jobs, etc. 15

16 Improving the Performance of the Field Different scenarios for development of the field can be tested (technically and economically). Now we are ready to optimize the lifespan of our Brown Field.

17 Conclusions Apply all the available data. Let everybody know about the geocelmodel construction and its progress, you never know who can provide valuable data from the field. Observe the rocks. Core or plugs extraction are expensive. Use them. Take them to Lab and perform tests. Use probability approach to deal with uncertainty. Go back and forth from geocelmodel to simulator as many times as necessary until the team feels it s the best approach to the Field. Use team brainstorming to imagine different scenarios for development and evaluate them (T &E). Don t lose focus: Improve production, Reduce costs, Optimize lifespan of the Field.

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