SPE 139222 SELECTION METHODOLOGY FOR SCREENING EVALUATION OF ENHANCED OIL RECOVERY METHODS

SPE 139222 Selection Methodology for Screening Evaluation of Enhanced-Oil-Recovery Methods M Trujillo, D Mercado, G Maya, R Castro, C Soto, H Pérez, V Gómez and J Sandoval, Ecopetrol S.A Copyright 2010, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Latin American & Caribbean Petroleum Engineering Conference held in Lima, Peru, 1–3 December 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 This paper presents a methodology for the selection of the enhanced oil recovery technologies that better applies to some group of fields using screening criteria The methodology has been integrated in a software in order to make repetitive analysis in an easier way, and has been applied for identifying the technologies whit higher technical potential of application in the Colombian Fields which have the biggest amount of oil in place (approximately 80%) The methodology incorporates oil and rock properties and the reservoir current conditions, besides the specific knowledge of the reservoir generalities and history In some Colombian fields, processes that use water, gas or steam have been applied; additionally, some other projects using water, gas, chemicals and air are in a design stage at this moment, however, more than 90% of the approximately 280 Colombian fields are still in primary recovery This is one of the main reasons for having an oil average recovery factor of about 21%, and it also states the need of using methodologies that allow identifying the best investment options The technologies considered in this analysis were: water injection, lean gas, rich gas, N2, WAG, CO2 (miscible and immiscible), polymer, surfactant – polymer, steam (cyclic and continuous) and some others such as CHOPS, VAPEX, WET VAPEX, SAGD, in situ combustion and electromagnetic heating The application of the methodology presented in this study allowed to identify the enhanced oil recovery technologies with higher potential for being applied in the Colombian fields with biggest amount of oil in place; it also generated a guide for the construction of every analyzed field development plan, which is presented as an example for the Cocorná heavy oil field The subject treated in this paper is more important for companies that own an important number of fields, and need to identify those with better characteristics for enhanced oil recovery projects in a quick and easy way; however, it is also very useful for companies that are beginning to develop any specific field Introduction There is different software applications in the oil industry that, besides the selection of the most technically applicable EOR process, can be used to obtain predictions, recovery factor estimations, etc., some of the mentioned software are: EORgui, allows to apply EOR screening criteria of nine methods to any field, and to quantify the incremental production of the applicable technologies using six different prediction methods The software is based on the Taber, Martin and Seright screening criteria Sword, was specially design to make quick evaluation of EOR potential, screening studies and predictions of EOR methods The screening techniques and prediction methods in the software are based on multi – criteria models, probed analytical solutions, industry experiences, field practices and experts’ knowledge in EOR applications SelectEORTM executes screening studies taking into account seventeen EOR processes and makes predictions using fourteen methods It was sent to the market in 2009 for the Alberta Research Council, and it is based on the prior software named PRIzeTM The screening criteria are based on a complete database which has had good acceptance for its effectiveness in the evaluation of EOR potential around the world 2 SPE 139222 Screening 2.0 is a software tool developed by the I.C.P of ECOPETROL S.A., and can apply screening criteria of eighteen EOR methods This tool considers the screening criteria of Lewin, Farouq Ali, Taber, Seright, NPC, McRee, Iyoho, Stalkup, SSI, E.C Donaldson, Leonard, Pri – Canada, Ganesh Thakur, William Cobb, Dusseult, Singhal, Geffen, Chu, Poett – Mann, between others IORSys (IOR – Predictive Software System) is a software tool developed by RIPED (Research Institute of Petroleum Exploration & Development, PetroChina), and its main application is evaluation of EOR potential The software consists of different modules: data management, screening methods, EOR potential evaluation and prediction The software tool presented in this paper executes screening criteria of nineteen EOR methods (based on the software Screening 2.0), and allows to obtain the analogs fields of any other supported in a data base of approximately 1000 fields It also applies the benchmarking methodology developed by Perez et al, and last, it estimates the behavior of water and steam injection With the use of this tool the engineer could be able of selecting the EOR method that technically applies to any field and / or formation, to identify EOR projects in analogs fields, to determine the probability of success of an specific method and finally to make analytical predictions The above applications will be shown by an example using the Colombian Cocorná Field, which is part of the Teca Field, and one of the Colombian oil fields with OOIP higher than 500 MMBO METHODOLOGY The methodology includes main aspects: binary technical screening, analogies, benchmarking and analytical prediction Binary technical screening is based on the comparison of certain properties of fluids and reservoir of a field under study with the criteria proposed by diverse authors through time, with the aim of determining which methods of improved recovery are feasible technically to apply in this field Properties such as porosity, permeability, viscosity, API, So, thickness, depth, reservoir temperature, pressure and lithology are analyzed Binary technical screening includes a great amount of methods of improved recovery that allow to apply it to different types of reservoirs (light, medium or heavy oil, deep or shallow reservoirs, etc) The contemplated methods are: Injection of water, gas (poor and rich), nitrogen, CO2 (miscible and immiscible), polymer, surfactant-polymer, steam (continuous and cyclic), and others like CHOPS, WAG, VAPEX, WET VAPEX, SAGD, combustion and Electromagnetic Heating The analogies are based on an analog model that allows to identify from a data base of approximately 1000 projects of application of methods of improved recovery if a specific technology EOR has been implemented under properties of fluid and reservoir similar to those in the field under study Once the analogs fields have been selected, it can be identified the best practices associated with the application of the recovery method and the lessons learned as well as with the problems related to the implementation of this technology The benchmarking methodology was developed by Perez et al1 who based it on the characteristics of successful steamflood projects, to develop a model to rank potential reservoirs They analyzed reservoir data using standard statistical methods for properties, such as: API gravity, initial oil saturation, reservoir temperature, porosity, initial pressure, depth, net pay, viscosity at reservoir condition, initial (at the beginning of steamdrive)- bubble point pressure ratio and average permeability The statistical model ranked the properties on a standardized score scale A predicted score near to one hundred indicates a high probability of success1 of the steam injection in the field under study The analytical predictions are realized for the methods: water injection and steam injection The following explains in more detail each of the components of the methodology 2.1 BINARY TECHNICAL SCREENING Screening criteria: The screening criteria are the most common, fast and easy tool to use to determine if a field/reservoir becomes a good candidate for implementing an enhanced oil recovery process In the specialized technical literature are SPE 139222 published a series of screening criteria for different recovery methods, which have been obtained from the experience gained from many worldwide projects This methodology considers the screening criteria of Lewin, Farouq Ali, Taber, Seright, NPC, McRee, Iyoho, Stalkup, SSI, E.C Donaldson, Leonard, Pri Canadá, ganesh Thakur, William Cobb, Dusseult, Singhal, Geffen, Chu, poett-Mann, among others Some methods have screening criteria of more than one author and the tool offers the possibility of selecting the set of criteria to carry out the evaluation The screening criteria are proposed by different authors and at different stages of maturity of a recovery process, therefore, special care must be taken with this aspect when the applicability of a method can not be ruled out if some of the screening criteria proposed by different experts or incorporated into commercial tools are not met2, in this aspect, the analogies and the benchmarking methodology play an important role Additionally, the knowledge and criterion of the engineer are the most important aspects Fluid and reservoir properties analyzed: The properties compared with the screening criteria are shown in Table Additional properties are compared, depending on the recovery method being evaluated The Table shows that the binary screening requires few data, which turns the methodology into a tool easy to apply, because in many occasions the fields not have sufficient information to realize more detailed studies After selecting the method or methods of recovery that technically apply to the field/reservoir by means of binary technical screening complemented with analogies and benchmarking methodology, the operating company would initiate the acquisition of the information necessary to carry out a more exhaustive study that can includes experimental evaluations, geological models, numerical simulation, economical analysis, etc, that would finally determine the feasibility of application of a particular method FLUID PROPERTIES Viscosity, cp API Gravity, ºAPI RESERVOIR PROPERTIES Current Oil Saturation, fraction Thickness, ft Permeability, mD Porosity, fraction Depth, ft Reservoir temperature, ºF Pressure, Psia Lithology Table Fluid and reservoir properties used to perform the binary technical screening Because pressure and fluid saturations change during the productive life of the field, it is important to evaluate these properties to the current conditions of the field/reservoir, to avoid a mistaken selection of the methods to apply to the field under study Score assignation: Each one of the 10 properties shown in Table are compared with the criteria of screening of the different authors A score between and is assigned A score of is assigned when the property is within the range established by Taber-Seright (1997), and zero when it falls in the opposite case When the property meets only part of the range, a score is assigned proportional to the rate of compliance The screening criteria of the other authors also are evaluated but are not considered for the assignment of the score Figure shows the procedure for assigning scores 4 SPE 139222 SCREENING CRITERIA FLUID AND RESERVOIR PROPERTIES FIELD UNDER STUDY (FIELD A) Viscosity, cp API Gravity, ºAPI Current Oil Saturation, fraction Thickness, ft Permeability, Md Porosity, fraction Depth, ft Pressure, Psia Lithology 600 12 0.55 100 150-300 0.28-0.32 2900-3200 500 Sandstone (SS) Vs Viscosity, cp API Gravity, ºAPI Current Oil Saturation, fraction Thickness, ft Permeability, Md Pressure, Psia Depth, ft Porosity, fraction Lithology TABERSERIGHT (1997) < 100000 8-25 > 0.4 > 20 > 200 NC < 5000 NE NE SCORE ASSIGNATION PROPERTIES Viscosity, cp API Gravity, ºAPI Current Oil Saturation, fraction Thickness, ft Permeability, Md Pressure, Psia Depth, ft Porosity, fraction Lithology TABER-SERIGHT Vs Field A 1 1 0.6666 1 0.9524 Score for each property Score of the method Figure Procedure for the score assignation in the binary technical screening Screening criteria exist in certain recovery methods that must be met to be technically feasible to apply it on a given field/reservoir It is the case of the depth in the steam injection, the minimum pressure of miscibility in the miscible gas injection, the temperature in the chemicals injection, among others This methodology takes into account these special criteria and from not being fulfilled one of them, the method would obtain the lowest score, although the other properties fulfills The methodology can be applied comparing the properties of a reservoir with the screening criteria of the 19 recovery methods included in it or only the methods that the user wants This depends on the knowledge that the engineer has about the field and the different methods of enhanced oil recovery Additionally, results can be analyzed by property and/or author, and it allows different types of graphics which can perform a more complete analysis of them 2.2 ANALOGIES In many cases the screening parameters alone not provide the necessary tools to select from a group of technologies which is most suitable to be implemented in a field That is why it is recommended to rely on the study of projects in fields that although they are not equal to the field in study, it presents certain similarity or analogy The analogies evaluation allows by means of a reasoning based on the existence of similar attributes between two different fields, to define a potential application of a determined recovery process This paper proposes a methodology which seeks to select from a database the project that has a greater similarity to the field/reservoir under study This is done through an expression that quantifies the different between some key properties of the fields in the database with the field that is under study The expression used for the ranking of the fields is as follows: n Sx = ∑F i =1 n i × 100 (Equation 1) SPE 139222 Where: Sx: Score obtained by a field of the data base with respect to the study field The major of all these values indicates the most analogous field to the field under study n: Number of properties to be taken into account when making the analogy Fi: Similarity factor between the value of a certain property of the field under study with respect to the value of the same property belonging to each one of the fields in the database This factor indicates how similar are the compared values and takes values between and A value near one indicates greater similarity and close to zero indicate that there is a greater degree of difference It is calculated as shown in the following equation: Fi = − pi − pie (Equation 2) max( pi − pie ) Pi: Value of the property to compare and belonging to a field in the database Pie: Value of the property to compare and belonging to a field under study max ( pi − pie ) The maximum of the differences found in a property by comparing all values of this property of the fields in the database with the field under study This is done with the objective that the similarity factor values are always between and For the special case when the value of the property is not a number but a chain of characters, the value of the similarity factor is zero when these characters are not equal 2.3 BENCHMARKING METHODOLOGY The benchmarking study included in this methodology was developed by Perez et al1 and allows to determine the probability of successful implementation of a particular recovery method in a field The Perez et al1 study was focused on the LMOSFs (Light/medium oil steamflood) and we extend it to the methods: Injection of water, chemical, steam, combustion and WAG, for which exist enough information in our analog database to apply this procedure Perez et al1 used successful LMOSF projects to create a database from which they selected certain key variables of the process to develop the study Because some variables could be more important than others, they developed a model that weighted each variable The distribution of the variables was performed from the coefficient of variation (CV), which is a dimensionless number This coefficient allows the determination of how disperse the values are with respect to the average The larger the CV for a certain property, the more dispersed it is and, hence, its relative importance is diminished Small values of CV for a property indicate greater "weight" (a greater importance) to this model1 Once the importance of each property was established, they performed a program to determine if the success of LMOSF projects could be predicted based on the previous experience The program calculates a value called “SCORE”, which varies between zero (0) and one hundred (100) As the SCORE approaches 100, there is a greater probability that the LMOSF will be successful Values near 50 indicate a possible failure Values smaller than 50 or near zero indicate a failure, or at least, a bigger risk1 2.4 ANALYTICAL PREDICTION METHODS The methodology uses the analytical models of Marx y Langenheim, Mandl y Volek, Closmann and the analytical model for heterogenous reservoirs designed by Diana Mercado (ECOPETROL-ICP) to determine the production oil rates and the recovery factor as a result of the steam injection process The prediction of the behavior of the water injection is performed with CGM method 6 SPE 139222 APPLICATION TO COCORNA FIELD Cocorná field, operated by Ecopetrol S.A., is located in the Middle Magdalena Valley (MMV) basin in Puerto Perales town, department of Antioquia It was discovered in 1963 by Texas Oil Company Some general information about the field is shown in Table FIELD COCORNÁ Sedimentary basin Drive mechanism Producing formations OOIP [Mbls] Wells Average spacing Artificial lift Middle Magdalena Valley Solution gas and weak water drive Transition, A, B and C of the Tune formation 96 Perforated wells: 57 Active wells: 35 Cored Wells: 10 acres Mechanical pumping Table General information of Cocorná field 3.1 Binary technical screening: The first step in the implementation of the methodology is the collection of reservoir and fluid data Table shows this information in the Cocorná field FLUID PROPERTIES Viscosity, cp API Gravity, ºAPI 722 13.1 RESERVOIR PROPERTIES Current Oil Saturation, fraction Thickness, ft Permeability, mD Porosity, fraction Depth, ft Reservoir temperature, ºF Pressure, Psia Lithology 0.64 132 1080 0.2-0.3 2500 109 275 Sandstone (SS) Table Fluid and reservoir properties of Cocorná field After introducing the initial data in the tool, the evaluation of binary technical screening is realized Fluid characteristics of the field indicate that it is heavy oil, therefore, the criteria of screening for the heavy oil methods were only evaluated: Steam (continuous and cyclic) injection and others like CHOPS, VAPEX, SAGD, in-situ combustion and electromagnetic heating According to the binary technical screening the methods that technically are feasible to apply in the field are: steam (continuous and cyclic) injection, CHOPS, combustion and electromagnetic heating Table summarizes the results These results determine the technical feasibility of implementing certain methods of recovery, however, need further analysis to determine which methods have a greater potential for application For this, we should analyze factors such as: the impact of implementing certain methods for future implementations of other processes, the influence of certain properties on the performance of each process, availability and management of injection fluids, maturity of technology, among others This analysis, for the Cocorna field, gives as a result methods of recovery with potential application, and in Table these are emphasized with blue color SPE 139222 RECOVERY METHODS CHOPS VAPEX Hybrid VAPEX Cyclic steam injection Steamflood SAGD In-situ combustion Electromagnetic Heating SCORE 0.533 0.6 0.5 0.889 0.921 0.891 0.5 Table Results of binary technical screening for the Cocorná field Figure shows the different possibilities from analysis of the results with binary technical screening through practical graphs, allowing the realization of analysis by author or property In this case, a graph is shown for continuous steam injection Additionally, reports with observations are generated about the fulfillment or not of each property Figure Analysis of the results for binary technical screening 3.2 Analogies: Given that the results of binary screening showed that the steamflood is the technology with the best expectation of implementation, analogies will be evaluated considering only steam flooding projects The results are shown in Figure Table shows de main characteristics related to each analog field/process In the tool, it is possible to access to the information of each of these fields as well as its characteristics and the information related to the injection project 8 SPE 139222 81.99 Fazenda Alegre (Fm.Urucutuca) 80.68 Tia Juana (Fm.Lagunillas Inferior) 79.89 Guapo (Fm.Cruse E & F) 79.46 Field Midway-Sunset (Fm.Marvic) 77.77 Placerita (Fm.Lower Kraft) 77.67 Midway-Sunset (Fm.Monarch) 76.1 Midway (Fm.Spellacy) 75.36 Midway (Fm.Potter) 73.68 San Ardo (Fm.Aurignac) 72.09 Coalinga (Fm.Temblor) 65 70 75 80 85 Score Figure Results of analogies for the Cocorná field Field Operator Country Start date Area, acres No Wells prod No Wells inj Pay zone Prev prod Proj matur Tot prod., b/d Enh prod., b/d Proj Eval Midway Chevron USA 1970 1,200 711 69 Spellacy Prim HF 9,400 9,400 Succ Midway-Sunset Aera Energy USA 1988 68 75 22 Marvic SS HF 1,151 1,138 Succ Midway Chevron USA 1964 1,214 2,039 225 Potter C HF 21,000 21,000 Succ Coalinga Aera Energy USA 1965 540 392 84 Temblor Prim HF 5,394 5,394 Succ Midway-Sunset Aera Energy USA 1984 15 Sub Lakeview Prim NC 15 Succ Tia Juana PDVSA E&P Venezuela 1970 1,692 25 Lagunillas Inferior HF 5,916 3,815 Succ Placerita Berry USA 1987 120 50 Fazenda Alegre Petrobras Brazil 2001 1,255 59 Guapo Petrotrin Trinidad Aug76 400 80 USA 1987 290 85 USA Jun-68 125 28 Coalinga San Ardo Aera Energy Aera Energy Lower Kraft Prim / Cyclic HF 3,000 2,700 Succ Urucutuca Prim HF 9,500 9,500 Succ 12 Cruse E & F Cyclic HF 792 792 Succ 21 Etchegoin Prim HF 1,384 1,384 Succ Aurignac SS NC 304 304 Succ 58 Table Some characteristics of the stemflooding processes in the analog fields to Cocorná field FUENTE: Oil & Gas Journal Report 2010 3.3 Benchmarking methodology: The benchmarking process for the Cocorná field was performed by the analysis of the properties: porosity, permeability, current So, temperature, depth, viscosity and API gravity Figure shows the results obtained According to the methodology, the score of 79.24, which is close to 100, classifies Cocorná as a potentially successful reservoir to apply steamflood technology SPE 139222 Cocorná Score : 79.24 Porosidad (f racc) Permeabilidad (md) 15% 20% 2% Prof undidad (f t) 3% Gravedad API del crudo Viscosidad del crudo (cp) 17% 19% Temperatura (F) 3% Saturación de aceite al inicio del proyecto (f racc) Figure Results of benchmarking methodology for the Cocorná field 3.4 Analitical prediction: The figure 5, shows the results of the predictions made with the Marx-Langenheim method TASA DEACEITEPRODUCIDO AREA CALENTADA 1.4 160 1.2 140 120 Qo (B/ D) Área (Acres) 1.0 0.8 0.6 0.4 80 60 40 0.2 20 0.0 0 500 1000 1500 2000 2500 3000 500 1000 1500 2000 2500 Tiempo (Días) Tiempo (Días) PÉRDIDASDECALORACUMULADAS FACTORDERECOBRO DEACEITE 3000 1.0 Factorde recobro (Fracción) 50000 45000 40000 35000 Qloss (MMBTU) 100 30000 25000 20000 15000 10000 5000 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0 500 1000 1500 2000 Tiempo (Días) 2500 3000 500 1000 1500 2000 2500 3000 Tiempo (Días) Figure Analytical predictions for the Cocorná field CONCLUSIONS The proposed methodology allows to identify in a quick, simple and low-cost way, the technologies that are susceptible to application in any type of reservoir 10 SPE 139222 The use of screening, analogies and benchmarking together, allows a more accurate perspective of the recovery methods with the greatest potential application, when you have little information of a field / reservoir The proposed methodology is a useful tool that helps the engineer in making decisions; however, the most important tool is the criterion and engineer's knowledge about their field and different methods of enhanced oil recovery From the application of the methodology to the Cocorna field it is possible to conclude initially that it is constituted in a good candidate to undergo a process of continuous steam injection Nevertheless, it should be noted that the thickness of sands of the field will be a critical parameter in the evaluation of the feasibility to implement the continuous steam injection REFERENCES 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 PEREZ-PEREZ, Alfredo et al Benchmarking of steamflood field projects in light/medium crude oils SPE 72137 2001 MERCADO, Diana Patricia et al SCREENING DE LOS MÉTODOS DE RECOBRO PARA LOS CAMPOS DE CRUDO PESADO COLOMBIANOS ECOPTEROL-ICP 2009 ALVARADO, Vladimir y MANRIQUE, Eduardo Enhanced oil recovery Field planning and development strategies 2010 TRUJILLO, Marta et al Screening de los métodos de recobro mejorado para los campos colombianos OOIP > 500 MMBO y aceite remanente > 200 MMBO ECOPTEROL-ICP 2009 MANRIQUE, Eduardo y WRIGHT, Jhon SCREENING METHODS HELP OPERATORS IDENTIFY VIABLE EOR OPPORTUNITIES The American Oil and Gas Reporter 2006 MANRIQUE, Eduardo et al WATER-ALTERNATING-GAS FLOODING IN VENEZUELA: SELECTION OF CANDIDATES BASED ON SCREENING CRITERIA OF INTERNATIONAL FIELD EXPERIENCES SPE 50645 1998 JIMENEZ, Ana María ANÁLISIS E INTERPRETACIÓN DE YACIMIENTOS SOMETIDOS A INYECCIÓN DE QUÍMICOS (SURFACTANTES, POLÍMEROS Y MISCELARES) MEDIANTE ANALOGÍAS Universidad Industrial de Santander 2009 JIMENEZ, Robinson ANÁLISIS E INTERPRETACIÓN DE YACIMIENTOS SOMETIDOS A PROCESOS DE INYECCIÓN ALTERNADA DE AGUA Y GAS (WAG) MEDIANTE ANALOGÍAS Universidad Industrial de Santander 2005 ALBAHLANI, A.M y BABADAGLI, T Review of the status of SAGD: Where are we and what is next? 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