Deep offshore oil production demands very high investments (CAPEX) so its development must rely on a careful planning. This frequently takes place in a setting with very limited amount of information due to high costs of appraisal operations. The figure becomes even more complicated when heavy oils are the target: low energy reservoirs require water flooding which, in turn, reflects in low recoveries and excessive water handling, not to mention other production problems.
This paper highlights different simulation studies that have been performed in order to set up an economical development plan for a 16 API 1700m water depth oil reservoir offshore Campos Basin. The main reservoir consists of a high thickness turbidite channel crossed by a N-S fault whose hydraulic conductivity is the main uncertainty. Vertically the reservoir is composed of three zones, where the upper one has a gas cap partially in contact with the two bottom ones. These structural complexities required a detailed study for positioning injectors and horizontal producers based on a decision tree analysis. The impact of other uncertainty variables was also identified and studied: horizontal permeability, vertical to horizontal permeability ratio, water-oil relative permeability and productivity index. Particular attention was given to the injectivity decline due to the planned produced water re-injection. Vertical and horizontal injection wells performances were compared in a scenario under strict geomechanical restrictions. The simulation model was also used to evaluate the possibility of developing marginal areas close to the main reservoir body.
The study leaded to a robust strategy for the water injection scheme. Risk and marginal reservoir analysis helped the decision of the features of the future production system in terms of oil and liquid processing capacity and adoption of some flexibility to make feasible the future development of marginal areas.
Exploration efforts offshore Brazil have been indicating important heavy-oil discoveries in deepwater reservoirs. The economic exploitation of these reservoirs presents technological and economic challenges that must be addressed. Therefore, the initial development plan must be defined through a detailed optimization study, considering economic indicators, oil recovery and risks 1, 2.
The development of Marlim Sul Field was planned in four modules: module 1 started in 2001 and has two production units producing 200,000 bopd. Module 2 will start the production through P-51 platform in 2008 and modules 3 and 4 are in development phase. These two last areas present special difficulties since they have oil viscosities greater than 20 cP at reservoir conditions. The introduction of new technologies could mean the solution for the feasibility of these projects.
Thus a research project was developed in the scope of Petrobras Offshore Heavy Oil Technological Program (PROPES) that comprised the following objectives: optimization of the drainage plan, taking into account the application of extended horizontal wells (around 800 m), evaluation of the use of high capacity plants for the processing of produced fluids and evaluation of the performance of artificial lift methods comparing the efficiency of gas lift and electrical submersible pumps. Studies related to the impact of the main N-S fault of the reservoir on the development plan, the consideration of uncertainties on rock and fluid properties and the analysis of the injectivity decline had also been performed.
This work focuses on the optimization of a development plan for Marlim Sul Field's third and fourth modules aiming at establishing a robust strategy encompassing all the geological and technological uncertainties.
Reservoir General Data
Marlim Sul Field is located in Campos Basin, distant approximately 120 km from north coast of Rio de Janeiro State, Brazil. It stands in water depths varying from 800m to 2600m in an area of 572 km2. Figure 1 depicts the field location.
The largest remaining reserves of heavy oil can be considered an important energy source for future supply. This means that heavy oil is a strategic resource for the future of energy industry. In order to produce these resources, a petroleum company has to invest from exploration to decommissioning, over a time-period that may reach several years.
The problem faced by managers is the correct valuation of sequential investment opportunities whose result will be known only many years ahead. The traditional method for valuation and decision-making is to compute the expected value of the mapped future scenarios with the help of a decision-tree, but its main drawback is that the correct discount rate is hard to estimate because it changes continuously over the nodes of the tree.
In this paper, we use the option-pricing approach, noting that after the success of seismic exploration, management has the option to invest in appraisal whose exercise price is the cost of wildcat wells. After the success of appraisal, management has the option to invest in development and production.
We apply the proposed model to the analysis of investment in a typical petroleum integrated project. We find different results and conclusions from those of the traditional NPV:
In this paper, we discuss the problem of sequential investment faced by managers of different oil and gas companies, especially in case of heavy-oil reserves located in ultra-depth water. We define here in this paper as heavy-oil that one with oAPI gravity of 15o to 19o and extra-heavy oil with 11o to 15o API gravity. Recent results from oil companies operating in offshore areas rank viscous oil those between 10 and 50 cP @20 oC; extra-viscous oil those between 50 and 400 cP; dead viscous oil those ranging from 400 to 5000 cP @20 oC; and dead extra-viscous oil those varying from 5000 and 50,000 cP @ 20ºC. Some other classifications of heavy oil can be found in Pinto et al. (2003) and Thakur (1997).
The business of heavy-oil is expected to grow in the future with the depletion of light oil reserves and because it is around 70% of the current world's total resource (DOE, 2007). In order to make use of this resource, there are at least two important technological challenges to overcome. First, it is the displacement of heavy oil up to production well and second, it is the pumping of heavy-oil up to the surface. Among the new technologies required for commercial production of these heavy-oil reservoirs in deep-water, new artificial lift devices and long horizontal wells can be detached, completed with efficient sand control mechanisms (Pinto el al.,2003, Trindade and Branco, 2005). Besides providing commercial value for the heavy-oil wells, it is expected that these new technologies will create a new value for such resources.
In managing new oil projects, the main problem is uncertainty in oil price and production reserves and, in addition, the decision chosen today will generate revenue or loss a long time ahead in the future. Over this period, several unexpected events may take place. Before addressing the managerial implications of the valuation and decision-making, it is worthwhile a brief discussion about the different phases of decisions process in a traditional oil project.
First, companies have to invest in exploration through the acquisition of seismic and geological data. In this phase, there are uncertainties in quality and quantity of data. In sequence, these data are analyzed and interpreted by the company's team of geoscientists and the decision will be to drill a wildcat or give up the opportunity.
This paper describes the implementation of a petroelastic model (PEM) based on Gassmann's equation to calculate seismic attributes into a commercial reservoir flow simulator. This implementation is the first step of a project to integrate time-lapse (4D) seismic attributes into an assisted history matching tool developed in a previous project.
The paper includes the description of the PEM and some implementation issues, such as the coupling of the model with the flow simulator with the purpose of using its basic calculated properties, discuss some user options (such as properties input through correlation or geoestatisticaly obtained maps) and the model variants and extensions (such as lithology influence and pressure effects). Three applications of this petroelastic model are shown: the first is a synthetic model based on outcrop data; the second is a 4D feasibility study for water injection monitoring in an offshore field; and the last one is a comparison between observed and calculated pressure impedances for an offshore field.
The resulting tool is applicable, for example, in 4D seismic feasibility studies, in seismic modeling for comparison with observed surveys and makes possible further implementations for incorporating the seismic data in assisted history matching.
The use of petroelastic attributes has several useful purposes1, such as feasibility of applying 4D seismic monitoring, optimize 4D seismic monitoring program and prepare more accurate production forecasts.
A possible workflow for applying 4D seismic in the monitoring of fluid flow in porous media follows the iterative steps2:
Steps 3 and 4 are unnecessarily cumbersome because most flow simulators do not calculate reservoir seismic attributes. As a result, information from the flow simulation Step 3 must be converted to a format suitable for analysis in the PEM Step 4.
In addition, errors may be introduced into the calculation of seismic attributes if fluid properties in the PEM do not match the corresponding fluid properties in the flow simulator, like using standard correlations of fluid properties.
These problems can be avoided if the PEM is incorporated into the flow simulator, eliminating the need of a third-party software to calculate the seismic attributes, so that it uses exactly the same fluid property model.
Fanchi1 shows the results for some reservoir management scenarios, applying successfully the petroelastic properties information calculated through an integrated flow simulator using the Gassmann's equation3, improving the reservoir management and monitoring processes.
Gosselin et al.4 also implemented an integrated flow simulator tool5 using the Gassmann's equation in a project to integrate 4D data into an assisted history matching process.
The ultimate aim of this project is to incorporate time-lapse seismic attributes into an assisted history match (AHM) tool, which combines efficient derivative calculation and robust optimization techniques, already developed in a previous project6 through an integrated reservoir flow simulator, facilitating a lot the viable use of this kind of data.
This paper presents a simplified economical analysis of PETROBRAS' experience with the pilot project for polymer mobility control in the Carmópolis field, and an evaluation of the world and Brazilian current scenario of this technology.
The positive results of this pilot and the new world scenario of the oil industry, shown here, assure great potential of this technology, especially in a time marked by a rising oil prices and growing environmental and social conscience.
The pilot project was aimed firstly to evaluate the fit of the polymer technology to Carmopólis field, considering the particular characteristics of the field regarding rock heterogeneities, oil type, water salinity, temperature, pressure, etc. A second goal was to obtain know-how in all the project phases like lab tests, design and operation in field scale and, finally, technical and economical analysis as a function of the additional oil recovered and the direct investment. This economic analysis is a starting point for more comprehensive economical evaluations.
This economic evaluation closed the sequence and will be important to the possible future unfolds. This evaluation was done with a special criteria because of the operational typical difficulties of this kind of project. All the investment is justified by the fact of polymer injection to be, according the literature, the easiest application and one of the lowest cost of the incremental oil and besides, the onshore experience is the first step for the future offshore field application.
This experience demonstrated that the injection process of polymer for mobility control is efficient even for heterogeneous reservoirs as Carmópolis field, and still, in a sustainable way, in other words, with increase of the oil production and reduction of the use of the water and consequentially of the water produced, and of the costs and of the environmental problems associated to this water, in agreement with the new world partner-environmental conscience.
The first experience by PETROBRAS with polymer was in 1969, Carmópolis field, in the so called "Pusher?? project, with the polymer injection in the main block that lasted until 1972. The final evaluation of this Project, just done in 1989 by PETROBRAS Research Center (1), generating many controversies relative the success, or not, of the process. Many questions came up at the time, among them the correct design of the injected polymer slug, the product select, the surface equipment and the generated data accuracy.
Years later, despite of the controversial of this experience, the process attractively increased even more with the technologic advantages reached by polymers stimulating the PETROBRAS to invest in new polymer pilot, again in the Carmopólis field (September/1997).
The principle involved in the polymer project process to the mobility control is well-known; however its application in field is directly connected to the reservoir selection as well as polymer and slug specification (2-7). Another important point of this kind of project is the evaluation of the results (8) that for being a long step and involving a big group, if it is not done with criteria can harm all the experience.
Polymer flooding in oil reservoirs has been performed for several decades around the world. The polymers act basically increasing the viscosity of the injected water and reducing the porous media permeability, allowing for an increase in the vertical and areal swept efficiency of the water injection and, consequently, increasing the oil recovery.
The main subject of the pilot projects in PETROBRAS was to gain know how in the process, for a possible future expansion to other reservoirs and even to offshore fields. Because of the volume of information about this pilot experience, results have been presented in parts. A first previous paper presented the lab work on polymer and pilot area selection among with the field pilot design from that laboratory physical simulation. Then, a second paper was devoted to the technical evaluation, i.e., the reservoir response in terms of injectivity tests, characterization with tracers and analysis of the positive changes found on production profiles (7, 8). Finally, a simplified economical analysis of this experience is presented here as well as an evaluation of the current scenario of this technology.
Ganga, Adriana de Oliveira (Petrobras S.A.) | Braga, Mario Sergio (Petrobras) | Silva, Edilon (Petrobras S.A.) | Braganca, Glaucia Holanda (Petrobras) | Maciel, Walter Becker (Petrobras) | D'Oliveira, Manoel (Petrobras S.A.)
Caratinga giant oil field is located in the central part of Campos Basin, Southeast of Brazil, in water depths around 1,000 meters. The total reserve is around 290 MM boe in these turbidite sandstones, 78% of which are within the lower Oligocene Reservoir (CRT100) and 22% are within Oligocene/Miocene and Eocene/Paleocene reservoirs. The CRT100 is a turbidite submarine fan of maximum thickness of 40 m, that was further cut by a NW-SE, Lower Oligocene submarine canyon, that have segmented the reservoir in two blocks: North Block and South Block. This canyon was further filled by the Oligocene MRL600/700 and the Oligocene/Miocene MRL330 sandstones. These canyon-filling sandstones constitute the Central Block. The development strategy for this field included a Pilot Phase in which three producer wells, one in each block, produced to a FPSO. The history match of this production data did not consider connectivity between the North and South Blocks of the CRT100 reservoir; although, seismic data have suggested possible reservoirs connection through the Central Block. Despite these features were represented in the 3D reservoir modeling, the transmissibility multipliers used kept these connections closed. The definitive production system, with 12 producers and 8 injection wells, started in February of 2005.
The extensive use of pressure down hole gauges and a dedicated reservoir team allowed the observation of very important new information about the reservoir hydraulic behavior. Among several other issues that have arisen, a good communication across the Canyon was confirmed, connecting the North and South Blocks. This effective hydraulic communication observed can be explained by the sand to sand juxtapositions between off-canyon and canyon-filling sandstones in some regions, whereas the low thickness
reservoirs, associated to geological faults, can justify the fluid flow behavior in other regions. These issues have been considered in the flow simulation model. The results are showing an increment on the total recoverable oil, since some portions of the canyon sandstones that used to have a low recovery volume, are now being swept by the water flooding.
Caratinga deep-water giant oil field is located on the southcentral part of Campos Basin, southeast of Brazil, in water depths from 850 to 1,350 meters (Fig. 1). The reservoir depths range from 2400 to 3200 m.
Fig. 1 - Caratinga Field location in Campos Basin
The total reserve is around 290 MM boe in these high quality siliciclastic turbidite reservoirs from the Tertiary, 78% of which are within the Lower Oligocene Reservoir (CRT100), and 22% are within Oligocene (MRL600/700), the Oligocene/Miocene (MRL330), and the Eocene/Paleocene (ENCOBR) reservoirs. The average gravity of the oil ranges from 20 to 29º API.
The CRT100, which is the main reservoir in the Caratinga Field, was cut in the Lower Oligocene, by a NW-SE submarine canyon that have carried part of the sands out of the Caratinga ring fence.
In mature fields, operators are often seeking ways to increase the hydrocarbon recovery, with the help of reputable service companies. Well stimulation continues to be, by far, the preferred method of achieving such goal. Operators and service companies are continually screening out technologies which will deliver the highest benefit/cost ratio for a particular stimulation well treatment, maintaining focus on operational and health, safety and environment excellencies .
This paper addresses the rebirth of a past hydraulic fracturing technique, born in the 50's, and how it is being successfully applied on onshore mature fields in Brazil: batch fracturing. It is effective due to several technological advancements on proppant density, becoming lighter than conventional frac sand and yet with sufficient mechanical properties to withstand bottom-hole environments. Batch fracturing is now contributing to equally efficient, and more economical well stimulation treatments, providing good economical returns to operating companies.
Batch-Fracturing had limited success in the past. This was due to the available frac fluid and proppant technologies at that time. It is desirable that proppants have low settling when carried by a fracturing fluid, from the time they are added into such fluid, until the end of the pumping process. Batch fracturing applications are on the rise, due to the new families of ultra lightweight proppants, with specific gravities ranging from 1.05 to 1.75. In batch fracturing, the proppant is added to the carrier fluid prepared in standard oilfield mixing tanks,
eliminating the need of specialized mixing equipment such as blenders. Less sophisticated equipment on location implies in lower operational and logistical costs. The carrier fluid ("frac fluid??) does not need to yield high levels of viscosity, and, by consequence, does not have a high load of chemicals (gelling agents, cross-linkers, related breakers…). With batch fracs it is possible to perform common but effective types of fracturing treatments, such as "skin-by-pass?? (a fracture that by-passes the damaged zone), and "partial mono layer' fracturing, both exemplified in this paper, through case histories.
Today, most of the producing oil and gas fields are considered mature. Although continually being redefined, a field is considered mature when its current level of hydrocarbon production has passed its past production peak. Associated with the reservoir's production depletion, there are other hydrocarbon recovery issues inducing operators to continually seek ways to overcome these natural effects. They look, with their subcontracted service companies, for cost effective techniques and technologies able to increase production and
This paper describes an implementation of method to optimize the production in intelligent wells varying the wells inflow control valves settings using an optimization algorithm coupled to commercial flow simulators. The optimization is based on direct search methods. The optimization algorithm was coupled with two different commercial flow simulators and has been applied in two real Brazilian offshore fields to quantify the benefits of intelligent wells over a base case with conventional completion. The first field has three horizontal wells, two producers and one water injector, completed in two zones totalizing six inflow control devices. In this case, different scenarios have been analyzed varying the downhole valves type - on-off and multi-position. The results have shown that the intelligent wells scenarios increased the recovery factor and reduced the production and injection of water when compared with the base case (conventional completion). The second field has fifteen wells - nine producers with binary valves and six water injectors with six-position valves - producing and injecting in two or three zone totalizing 39 downhole valves to be optimized. In this case, the results have shown a significant increase of the expected cumulative oil production when compared with the base case.
The intelligent well technology provides the capability to remotely monitor and manage multiple production zones independently, reducing the cost of wells interventions, accelerating the production and reducing the injection and production of water. The ability to control multiple production zones comes from downhole inflow control valves. These devices may be binary (on-off behavior), or multi-position, choking the production zone with a discrete number of positions, or infinity variable position.
The benefits of the intelligent wells technology were shown in practical applications1-6 especially for multiple-zone producing commingled. During the operation with intelligent wells, one possible approach is to react when problems occur, for instance, choke the production zones with high water cut. Yeten et al.7 has called this approach as reactive control strategy. Another approach is to use the intelligent completions in conjunction with a predictive reservoir model. This model may be coupled with optimization algorithms to define production strategies that maximize the value of the field.
Some previous authors have studied the production optimization with intelligent wells. Brouwer et al.8, have presented a methodology that maximized sweep in a water flood study. The strategy was based on choking the segments with highest productivity index and redistributing the production in others segments. Brouwer et al.9, have applied the optimal control theory for production optimization. Yeten et al.7 have used a conjugate gradient optimization method coupled with a reservoir simulator to optimize the production with intelligent wells. They have proposed to divide the simulation into several steps of optimization. Ajayi et al.10 have applied an optimization process based on derivatives calculated as the change of the production rate of undesired reservoir fluid, water or gas, with the correspondent change in the desired fluid, oil or gas. The process corresponds to choke the zone with highest derivatives values in each time step. Naus et al.11 have proposed an optimization strategy with infinitely variable inflow control valves using a sequential linear programming to maximize production at a specific moment in time.
This paper presents an implementation of method to optimize the production in intelligent wells varying the wells inflow control valves settings using an optimization algorithm coupled to commercial flow simulators. The optimization is based on direct search methods. This kind of algorithm has some advantages in this case: the algorithm is based only in objective functions evaluations, this fact allows to consider the flow simulator as an external program like a "black box??; the algorithm permits to model binary and multi-position downhole valves, differently of gradient-based algorithms where is difficult to model problems with a finite number of discrete solutions; and the algorithm takes advantage in a grid computer environment, because the objective function evaluations can easily be done in parallel.
The main objective of this paper is to describe the integrated management process in Namorado field, a shallow water field in Campos Basin, Brazilian continental margin consisting on a multidisciplinary planning, a comprehensive diagnosis of the problems and a full set of corrective actions.
The steps include tools as wireline production and saturation logs, pressure and production tests, a suitable schedule of tubing changes, perforations in unshot oil intervals and abandon of swept intervals.
Moreover, a rigorous control of mass balance on injected and produced volumes is performed, as a permanent concern of the whole production asset, resulting in a politics of gradual increase in injected water volume and, consequently, an increment in the oil production.
It also includes periodic squeezes of an inhibitor in order to prevent Barium sulfate scaling and changes in the drainage strategy as the convertion of wells from producers to injectors and vice versa.
This management is performed by an integrated teamwork: Reservoir, Production, Workover, Lifting and Economics. It has shown remarkable results as the maintainance of the oil production and the reservoir pressure at the same level during the last twelve years.
Namorado field is located in the central portion of Campos Basin at water depths from 120 to 270m and is about 80 km distant from the São Tomé Cape, in the Northern coast of the Rio de Janeiro State, Brazil.
Discovered in December 1975 by the wildcat 1-RJS-19, the accumulation was satisfactorily delimited by twelve appraisal wells in the ten subsequent years.
The development phase of the concession occurred from 1983 to 1989 and involved the drilling of 48 wells, four of them were not used due to operational problems. Now, among the 33 producing wells, there are 30 wells with dry Christmas tree and 3 satellite wells with wet Christmas tree.
The oil production began in 1979 by a temporary production system to a FPSO. The definitive system, implemented after 1983, consists of two fixed platforms - PNA-1 and PNA-2, the first one with 10 oil producers and six water injectors, the second with 23 oil producers, three water injectors and one gas injector.
Initially, Namorado reservoir presented solution gas as primary production drive. In order to increase the recovery factor, in 1984 it was implemented seawater injection as a secondary recovery mechanism and also gas injection after 1997.
The lifting method is mainly gas lift and there are few surgent wells. The oil is then transfered to the continent through PGP-1 platform (Garoupa field), while the gas flows directly to the continent through a large pipeline.
The main reservoir, informally named Namorado Sandstone, belongs to the Upper Albian-Cenomanian transgressive sequence of Macaé Formation. It corresponds to clean sandstones, medium to coarse grained, predominantly massive, amalgamated up to 150m of thickness, deposited by turbidity currents in a background environment of sedimentation of marls and calcilutites1.
The reservoir presents a domic structure dipping to the North and to the East and pinching out to the North and to the South, as shown in the map of the Figure 1.
The presence of NW/SE faults compartimentalizes the field in at least three structural blocks (from West to East): the main, the adjacent and the marginal one, as seen in Figure 2. This structural model of assigned blocks is confirmed by the detection of several oil/water contacts. During the subsequent depletion of the reservoir, all blocks have shown pressure and fluid communication.
In almost all wells, it is possible to recognize three sequences of amalgamated turbiditic sandstones separated by discontinuous sequences of marls. Wireline formation tests in the development wells pointed out that the three sequences have a differential depletion among them (5 to 10 kgf/cm2), characterizing a small level of reservoir heterogeneity.
Mixing of sea- and production waters during waterflooding of offshore oil reservoirs results in reaction of barium and sulphate ions causing precipitation of barium sulphate with consequent rock permeability decrease and well productivity decline. The reliable productivity decline prediction is based on mathematical modelling with well-known model coefficients. The sulphate scaling system contains two governing parameters: the kinetics coefficient characterising the velocity of chemical reaction and the formation damage coefficient showing how the permeability decreases due to salt precipitation.
Previous works have derived analytical-model-based method for determination of both coefficients from breakthrough concentration and pressure drop during laboratory coreflood on quasi steady state commingled flow of injected and formation waters. The current study extends the method and derives formulae for calculation of two scale damage coefficients from just pressure drop measurements during two corefloods with two different ratios "formation water : seawater??.
Data from series of three corefloods on commingled injection with three different "formation water : seawater?? ratios, were treated. Equality of scaling damage parameters as obtained from three different floods in similar artificial cores validates the method proposed.
In deepwater offshore operations where seawater injection is a common development practice, barium, calcium, and strontium sulphate scale deposition is a serious concern. Barium sulphate and related scale occurrence is considered a serious potential problem that causes formation damage near the production-well zone1-5. The major cause of sulphate scaling is the chemical incompatibility between the injected seawater, which is high in sulphate ions, and the formation water, which originally contains high concentrations of barium, calcium, and/or strontium ions6-9.
A reliable model capable of predicting such scaling problems may be helpful in planning a waterflood scheme. It may also aid in selection of an effective scale prevention technique through the prediction of scaling tendency, type, and potential severity.
A reliable predictive model must use well-known values of the model coefficients.
The mathematical model for sulphate scaling contains two phenomenological parameters: the kinetics coefficient from active mass low of chemical reaction showing how fast the reaction and precipitation occurs, and the formation damage coefficient reflecting the permeability decrease due to sulphate salt deposit10-15.
Both coefficients are phenomenological parameters depending on rock surface mineralogy, pore space structure, temperature and brine ionic strength. Therefore, they cannot be calculated theoretically for natural reservoirs and must be determined from laboratory corefloods.
Reagent and deposition concentration profiles during reactive flows are non-uniform. So, the sulphate damage parameters cannot be directly calculated from laboratory measurements. They must be determined from laboratory coreflood data using solutions of inverse problems.
The quasi steady state commingled corefloods by sea- and formation waters were performed by numerous authors16-19.
The kinetics coefficient can be calculated from breakthrough concentration in quasi steady state coreflood with commingled injection of sea- and formation waters. Then the formation damage coefficient can be determined from pressure drop increase during flooding20,21.
The pressure drop measurements are simple and robust while breakthrough concentration determination is a cumbersome laboratory procedure. Therefore, often concentration data are unavailable17. Availability of the method for characterisation of scaling damage system from pressure measurements would simplify the laboratory procedure on sulphate scaling studies. This is the subject of the current paper.
Based on analytical model for commingled coreflood by sea- and formation waters, the current paper develops a method to determine two scaling damage parameters from pressure measurements during two floods with different "formation water : seawater?? ratios.
In petroleum industry, scarce information is available at the time of adopt the exploitation strategy, and the expected production profiles comprise a high level of uncertainty. Depending on the range of the uncertainty variables, the best decision may be to collect more information by drilling more wells, performing a new seismic acquisition or making long term tests. But, sometimes, the best way to protect the project is to assume an uncertainty-proof development strategy. These ideas were applied to help decision in two real cases, in Marlim Sul field, Campos Basin, Brazil. In the first case, the main uncertainty source is the quality of the flow transmissibility between producers and injectors wells. If that communication is restricted, the production decline is more accentuated and the best strategy would be to place the injectors nearer the producers, although the displaced oil is reduced. In order to elect the best strategy, we have compared two different plans containing different positions of injector wells, applied to three different scenarios of flow transmissibility. In the second case, we have a channeled reservoir, with an extensive fault in the middle, the transmissibility along which is unknown. In a scenario of good communication, the best strategy is to position the injectors on one side and the producers on the other side of the fault. But in scenarios of restricted communication, the best scheme could be to place injectors and producers on both sides of the fault. To make the best decision, we have used different plans, applied to different scenarios. The results demonstrate that, in both cases, the alternate plan has not the higher net present value (NPV) in the moderate scenario, but presents the higher expected monetary value (EMV), having also a lesser sensitivity to the reservoir uncertainties, being more protected to the risk. In both cases the original plan has been abandoned and the alternative plan started being implemented.
The definition of the development project of an oil field is generally made with basis on insufficient information and under conditions of a great uncertainty as to the geologic parameters that characterize the fluid volumes and the flow properties. The adopted strategy is generally the one that produces the maximization of the fluids recovery, or the maximization of the economic parameters, when applied under the conditions regarding the most likely scenario. This scenario comprises the most representative image of the reservoir, with the most expected values of the properties related to the geometry and the flow of fluids in porous medium. After that, the analyses for characterization of uncertainty in the production curve, and also in the economic parameters, are carried out, with basis on the previously fixed project.
But this strategy may not be the most adequate, mainly if the uncertainties comprise a substantial range and if the application of the same strategy, under the conditions of the pessimistic scenario, reveals very serious consequences and very low economic results. An alternate strategy, less subject to these uncertainty sources, could be a more adequate option, even being economically less valuable and less appealing in the moderate scenario.
The purpose hereof is to present the application of a methodology of comparison and decision upon the best strategy for the recovery of oil, in scenarios of great uncertainty in the reservoir properties. The target field is situated in Campos Basin, Brazil, and two of its main development projects have been analyzed.
In the items hereafter some details on the field and its reservoirs, its main uncertainty sources and the strategies for the recovery or oil are presented. Following is it described the methodology of comparison of the strategies and, at last, the results of their application in two projects of the field.
Proposal of the problem: the field and its projects
Marlim Sul field is a turbiditic complex formed by channels, lobes, crevasse and spill deposits1. It is composed of fifteen reservoirs blocks of eocenic, oligocenic and miocenic ages, with excellent characteristics of porosity and permeability, and oil ranging from 15 to 25 API.