DIANA CORAL, MARCO RUIZ

Transcription

1 METODOLOGÍA DE ELECCIÓN Y MODELO DE DISEÑO DE TRATAMIENTOS ÁCIDOS PARA REMEDIAR DAÑO DE FORMACIÓN POR FINOS EN ARENISCAS. SELECTION METHODOLOGY AND PERFORMANCE EVALUATION OF AN ACID TREATMENT TO REMEDY FORMATION DAMAGE BY FINES IN SANDSTONES DIANA CORAL, MARCO RUIZ Petroleum Engineer, Universidad Nacional de Colombia, Medellín. decoralr@unal.edu.co Ms.c Chemical Engineering, Universidad Nacional de Colombia, mruizs@unal.edu.co ABSTRACT: Remediation of damage has two important aspects to consider: Choose a treatment and predict performance. Acid treatments options can be endless. Selectin the best treatment requires a compatibility study between treatmentformation and treatment-fluids reservoir. In a compatibility study are important mineralogy, pressure, temperature and petrophysical properties. Once treatment is chosen, the performance of acid formation is studied. The amount of acid to be used, velocity, concentration and injections pressure are essential to know. Analysis treatmentformation interaction can differentiate between success and failure of a process of remediation. In order to replace the trial and error method is required a coupled model. Base model for choosing the best treatment is builds on the methodology proposed by Kalfayan. As opposed to Kalfayan, in this study, different scenarios to conventional acid (HCl-HF) are studied. Moreover, Acid-formation interaction model is realized with four parameters model by Bryant. This model considers four chemical reactions between acid, quartz and aluminosilicates. Results of the modeling allow a useful tool in the design of remedial treatments of fine in sandstones and their interaction whit the formation. 1. INTRODUCTION Successful practice remediation of damage wells depends to experience service provider. Only 3 out of 10 stimulation operations are successful. Treatments to remedy formation damage are chosen by trial and error tests and only some of the options are evaluated (1,2). In addition, design is limited to the laboratory results and forgets to contemplate operational details and compatibility. Remedial procedures are done with design variables obtained on a laboratory scale. The north of the ongoing operation is monitored in real-time under the criterion of injection pressure decrease as an indicator of successful remediation (1). Stimulation operation becomes an empirical scenario and it lacks a treatment design methodology. Several methods are used to remedy formation damage by fines in sandstones. Injecting acid treatments into the formation with a pressure below fracturing pressure is known as matrix acidification. Acid dissolves particles that restrict the flow (3). Two important aspects in the matrix acidification are: choice of treatment and the prediction of acid performance in the formation. Acid treatment options can be infinite and best treatment selection requires a compatibility study between the treatment and mineralogy, pressure, temperature and petrophysical properties. Then, predict the performance of the acid in the formation is necessary. Study of reaction kinetics avoids potential failures in stimulation.

2 ESCUELA DE VERANO NATIONAL AND INTERNATIONAL PANORAMA Representative cases of damage formation by fine are found worldwide. For example: Ceuta in Lake Maracaibo, Venezuela, Wilmington in Los Angeles, California, The Ewing Bank 873 in the Gulf of Mexico, Gullfaks In the North Sea, Messla in Libya, Bastrykskoye and Zichebashskoe in Russia and the Duri Steamflood field in Sumatra, Indonesia (4 6). In Colombia presents fine damage in the fields: Yariguí- Cantagallo in the Magdalena basin, Ocelote, Castilla, Caño Limón and Cusiana in the Llanos Orientales, Orito, Juanambú, Carbe, Sucio, Quiriyana, Churuyaco, San Antonio and Sucumbíos producers of Villeta and Caballos formations in Putumayo and Nariño. In a recent study by National University of Colombia about diagnosis formation damage by fines in Colombian sandstones was found fields with problems of migration and swelling of fines (7). In Table 1 one representative well per field was reported. Table 1.Wells whit formation damage by fines in sandstones, following (7) POZO Critical flow (cc/min) Critical Radio (ft) MAX DAMAGE (S) Acae Apiay Castilla Cupiagua NW La Cira Orito San Antonio Sucumbíos Tenay Casabe Quiriyana TREATMENTS SELECTION METHODOLOGY Acidification process has stages depending on the compatibility treatment-formation to be achieved (1). In each stage proposed by Kalfayan, inference methods were applied to know the appropriate conditions of choice of treatments and additives. Figure 1. Steps Kalfayan Methodology (1) Information collected is organized into diagrams for make up a decision tree easy to take into a programming language. For each step treatments are evaluated. An example about selection preflush and principal treatments in high permeability is in the Table 2:

3 18 Table 2.Scenery for Preflush and Principal Treatment, following (1) Treatment Conditions and units Preflush Principal Treatment Permeability > 100mD Quartz [%] >80% ^ Clays [%] <5% 15% HCl 12% HCl 3% HF Clays [%] [5%,10%] ^Feldspars [%] <10% 10% HCl 7.5% HCl 1.5% HF Clays [%] >10% 5%-10% HCl 6.5% HCl 1% HF Feldspars [%] >15% 15% HCl 13.5% HCl 1.5% HF Feldspars s [%] >15% ^Clays [%] >10% 10% HCl 9% HCl 1% HF Chlorite [%] >5% 5% HCl 3% HCl 0.5% HF Computational structure and Input data of selection treatment methodology is summarized in Figure 3 and Table 3. Start Input data Readjust Input data Treatment selection Does it meet specific conditions? Yes Response assessment Recommend treatment Not Tabla 3. Input data Input data Mineralogy Crystallization temperature of paraffins Reservoir temperature Hydrogen sulfide Index of colloidal instability Emulsions Wettability Permeability Potassium Calcium Sodium Barium Bicarbonate Sulfate Liquid production flow Critical flow Figure 2. Computational model of election treatments Three variables for the evaluation of software response are included with the recommended treatment: Score A1, quantifies the reliability of the software response as a function of the decision tree information; Score A2, quantifies the reliability of the software response as a function of the input data; Score A3, quantifies the reliability of the software response as a function advantages and disadvantages of the treatment. 6. INTERACTION ACID-FORMATION MODEL Four parameters model considers three minerals and two acids in an acidification process. Mineral 1 collect fast reaction minerals, Mineral 2 are slow reaction minerals and Mineral 3 is silica gel. Acids are hydrofluoric acid (HF) and hexafluorosilicic acid (H 2SiF 6). Stoichiometry is developed (8):

4 ESCUELA DE VERANO 2017 [1] [2] [3] [4] Mass balance for acid and minerals in linear coordinates generates equations 5 and 6, respectively. [5] Equation 5 is used to model the acid spending in the formation. Where is the porosity, is the acid concentrations, is the time, is the Darcy velocity, is the reaction rate constant, is the specific surface area per unit volume of solid and the volume fraction for mineral. [6] Equation 6 is used to model the mineral dissolution in the formation. Where is the molecular weight of acid and is the density of mineral. is the dissolving power, 5. RESULTS A software response for Pickling for one well whit formation damage by fines can be: 1. Pickling: - 7.5% HCl + Corrosion Inhibitor: 0.5%-5% Formic Acid + Iron Control: 5% NH4Cl + Sulfide Inhibitor + Aromatic Solvent Score A1: 100 Score A2: 100 Score A3: 65 el diseño de tratamientos In this example, treatments are chosen for the first step of acidification. Treatments for other steps are omitted in this opportunity. Analysis of results is below: - Only compatible treatment for pickling step was 7.5% HCl - Treatment requires additives: corrosion and sulfide inhibitor, iron control and aromatic solvent - Reliability of software response is 100%, Score A1. - Available information from the well guarantees 100% the response of the software, Score A2. - Treatment is viable 65%, Score A3.

5 From interaction model between formation-acid is expected to obtain: Permeability, Skin effect, concentration acid, concentration minerals, porosity curves and design variables like volume acids, pressures and others. For now, one curve about change skin is indicated in figure 3. This image was obtained of reference (2). Simulation whit two models difference was obtained: Lumping model and two parameters model. Figure 3.Skin Effect vs Injection Volume Acid. Taken of (2) 6. CONCLUSIONS - Software allows the choice of acid treatments and modeling of the interaction of acid with the formation. Software enables to evaluate compatibility between acid whit mineralogy, yield fluids, organics and inorganics substances; to get the best treatment. Software predicts mineral dissolution, acid wear and change in porosity, permeability and skin. Evaluation of the reliability of the software response generates realistic sceneries whit real results. All this characteristics can increase from 7 to 3 the number of successful stimulations. 7. REFERENCES 1. Kalfayan L. Production enhancement with acid stimulation. 2nd ed. Quinn T, editor. PennWell Corporation. Tulsa, Oklahoma: PennWell Corporation; p. 2. Economides MJ, Nolte KG. Reservoir Stimulation. 3rd ed. Kapitan E, editor. Sugar Land, Texas: John Wiley & Sons Ltd; Hill a D, Schechter RS. Fundamentals of Acid Stimulation. In: Economides MJ, Nolte KG, editors. Reservoir Stimulation. 3rd ed. Texas, Austin; p Hibbeler J, Garcia T, Chavez N. An Integrated Long-Term Solution for Migratory Fines Damage, SPE SPE Lat Am Caribb Pet Eng Conf. 2003;(April): Colmenares FJ, Padron A, Bennaceur K. Evaluation of Treatments for Control of Fines Migration in the Ceuta Field in Venezuela, SPE Soc Pet Eng J. 1997;(October): Chavez N, Colmenares O, Pena AA, Fuenmayor A, de Sousa V, Miquilena E, et al. Optimal Practices to Remediate and Control Fines Migration in Inland-Water Wells in the Maracaibo Basin, West Venezuela. SPE Int Oil Conf Exhib Mex. 2007;(June): Zabala R. Un Modelo de Base Fenomenológica Para Escalar a Nivel de Yacimiento el Impacto Sobre la Producción de Fluidos del Daño de Formación por Migración de Finos. Universidad Nacional de Colombia- Medellín; Li C. Fine Scale Sandstone Acidizing Coreflood Simulation. 2004;138. Available from: