石油工程师协会技术年会论文spe166097.pdf

SPE 166097 High Pressure Data and Modeling Results for Phase Behavior and Asphaltene Onsets of GoM Oil Mixed with Nitrogen Odd Steve Hustad Statoil ASA NTNU Na Jenna Jia Schlumberger DBR Technology Center Karen Schou Pedersen Calsep A S Afzal Memon Schlumberger DBR Technology Center Sukit Leekumjorn Calsep Inc Copyright 2013 Society of Petroleum Engineers This paper was prepared for presentation at the SPE Annual Technical Conference and Exhibition held in New Orleans Louisiana USA 30 September 2 October 2013 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 high pressure PVT measurements and equation of state EoS modeling results for a GoM oil and for the oil mixed with nitrogen in various concentrations The data includes 1 Upper and lower asphaltene onset pressures and bubble point pressures for the reservoir fluid swelled with nitrogen At the reservoir conditions of 94 MPa 13 634 psia and 94 C 201 2 F asphaltene precipitation is seen after addition of 27 mole of nitrogen 2 Viscosity data for the swelled fluids showing that addition of nitrogen significantly reduces the oil viscosity 3 Slim tube runs indicating that the minimum miscibility pressure of the oil with nitrogen is significantly higher than estimated from published correlations The data has been modeled using the volume corrected Soave Redlich Kwong SRK and the Perturbed Chain Statistical Association Fluid Theory PC SAFT EoS While both equations provide a good match of the PVT properties of the reservoir fluid PC SAFT is superior to the SRK EoS for simulating the upper asphaltene onset pressures and the liquid phase compressibility of the reservoir fluid swelled with nitrogen Nitrogen gas flooding is expected to have a positive impact on oil recovery due to its favorable oil viscosity reduction and phase behavior effects Introduction Oil exploration is going into regions of more extreme conditions and large oil deposits 0 3 to 4 billion BOE are discovered in deepwater 2 000 m 6 500 ft Gulf of Mexico GoM Many of these deepwater reservoirs were formed during the Paleogene geological period lower Tertiary and are posing a significant challenge to exploit These reservoirs are found at approximately 8 000 m 26 000 ft true vertical depth TVD and consists of Turbidite deposits under laying thick salt deposits The salt deposits pose significant challenges for seismic interpretation The oils are highly undersaturated with low bubble point pressure 17 MPa 2 500 psia and fairly reasonable temperatures 100 C 212 F Undersaturated oils have little expansion energy Characteristic for these reservoirs are also their low permeability 1 30 mD The high initial pressures 125 to 175 MPa 18 000 to 25 000 psia in these reservoirs make it necessary with a primary production by pressure depletion However producing these reserves by pressure depletion will only result in recovery factors in the range of 6 to 12 These low recoveries with large in place oil volumes give incentives to investigate alternative drainage strategies to obtain an Increased Oil Recovery IOR Water or gas injection processes are traditional IOR processes However making these processes profitable presents some challenges High cost wells 350 million USD per well limits the number of wells that can be drilled for 2 SPE 166097 a particular reservoir Injectivity in low permeable formations may hinder getting injection fluids into the reservoir This is more severe for water than for gas especially when the displacement distances are taken into consideration For these highly undersaturated reservoirs gas injection may lead to asphaltene precipitation in the reservoir Understanding these phenomena and enabling appropriate forecasts of the impact of the gas injection is highly challenging The extreme conditions present other technical challenges which need to be overcome 1 The well technologies and reservoir technologies all have their specific technical challenges The DeepStar technology development project managed by Chevron and supported by several operators is a forum for advancing deepwater technologies 2 It is highly desirable to have the capability to perform high pressure measurements and it is important that results from such measurements are made available to the oil community Gas injection is a proven IOR process that can be economical and increase oil recovery Gas injection will make the reservoir fluid swell and will therefore help maintain the reservoir pressure and prolong the production rates Gas injection may however cause asphaltene precipitation and its impact to reservoir dynamics needs to be better understood Asphaltene precipitation phenomena have been studied by many authors 3 9 Presented below are results from a phase behavior study on GoM oil at high pressure The oil has been mixed with varying amounts of nitrogen and its properties measured Fluid compositions asphaltene onset and disappearance pressures are presented along with constant mass expansion CME results oil viscosities and slim tube measurements The results show that two liquid phases are formed prior to asphaltene precipitation and the emergence of a gas phase at 94 MPa The oil viscosity is reduced by a factor two during the swelling process The minimum miscibility pressure is significantly higher than results obtained from correlations in the literature 10 13 Phase equilibrium modeling of the measured data is presented using the Soave Redlich Kwong14 SRK EoS and the PC SAFT15 EoS The established EoS models were able to reproduce the measured data The PC SAFT EoS is slightly superior to the SRK EoS Phase Behavior Measurements In depth studies are required to understand the possible outcome of gas injection into low permeable Turbidite formations in high pressure GoM reservoirs The first step in this study is to map the phase behavior properties of the selected oil when mixed with nitrogen gas and to validate the measurements by modeling the data In this study nitrogen N2 is used as injection gas The phase behavior studies are at high pressures 94 MPa for varying concentrations of N2 A similar study has been conducted by Gonzalez et al 3 where variations in pressure and temperature were the main focus A TBP distillation was performed on the Stock Tank Oil STO sample to obtain data for the molar concentration molecular weight and density of the heavy components of the oil The results are listed in Table 1 The STO was recombined with a synthetic gas to obtain single phase reservoir oil the compositions and properties of which are shown in Table 2 Titration at 94 MPa and 94 C was conducted with N2 to obtain the Asphaltene Onset Concentration AOC During the N2 titration test an unknown second liquid phase appeared at 24 26 mol nitrogen added The second liquid phase seemed to have similar density as the first liquid phase Asphaltene precipitation was observed at 26 to 28 mol nitrogen added Figure 1 shows pictures taken from a High Pressure Microscope HPM at two conditions with 26 and 28 mol added nitrogen A Solid Detection System SDS analysis was also performed to confirm the visual results Table 3 presents the phase volumes from the swelling of the oil with nitrogen The oil volume is increased by 12 prior to asphaltene precipitation 28 mol N2 added at 94 MPa and 94 C Four additional fluid mixtures were created with varying amounts of nitrogen The original recombined oil labeled M0 had a nitrogen concentration of 0 121 mol The first three of the additional samples contained respectively 8 853 M1 17 244 M2 and 25 925 M3 overall mol of N2 The last M4 mixture with 67 mol overall N2 concentration split into two phases at 94 MPa and 94 C where the vapor and liquid nitrogen mol were 79 937 and 38 231 respectively SPE 166097 3 The asphaltene onset pressure AOP saturation pressure and asphaltene disappearance pressure ADP were measured for these fluid systems and are summarized in Figure 2 and Table 4 The AOP increases approximately linearly with increasing nitrogen concentration The ADP is low as compared to the saturation point and first decreases and then increases as the overall nitrogen content increases Once the gas concentration in the oil gets below a limiting value at ADP due to pressure reduction the asphaltene will redissolve Redissolution of asphaltene generally takes some time In the experiments with precipitated asphaltene Mixtures M1 M2 and M3 enough time was probably not taken for complete equilibrium to be reached Thus a probable explanation for the observed decrease in ADP may be kinetic effects Fig 1 HPM pictures of a second liquid phase with 26 mol added N2 and b asphaltene precipitation with 28 mol added N2 Fig 2 p x phase envelope for reservoir fluid swelled with nitrogen at 94 C Constant Mass Expansion CME experiments were performed for four of the five mixtures The results are illustrated in Figure 3 The following was observed a The relative volume curves become less abrupt at the saturation pressure as the concentration of nitrogen increases This is due to the oil becoming more volatile b Above the saturation pressure the oil density increases almost linearly with pressure and the linear trend becomes more pronounced as the concentration of nitrogen increases c The slope of the Y factor is similar for the M0 M1 and M2 mixtures but is different for M3 which is a mixture close to the AOC at 94 MPa More asphaltene is precipitated for this mixture affecting the measured volumes below the saturation pressure d The compressibility pattern for the recombined reservoir fluid deviates from that seen for the fluids with added nitrogen M1 M2 and M3 The slopes of the compressibilities for the latter three mixtures are fairly similar The oil viscosity was measured with an electromagnetic viscometer EMV model SPL440 As can be seen from Table 5 and Figure 4 the oil viscosity as a result of the N2 swelling dropped to half its original value Once an equilibrium vapor phase was formed the equilibrium oil viscosity increased to a value slightly above its original value This is explained by lighter and intermediate components from the oil phase entering into the nitrogen rich equilibrium vapor phase At 94 MPa the oil viscosity changes linearly with nitrogen concentration during the swelling process 0 20 40 60 80 100 120 140 010203040506070 Pressure MPa N2Concentration mol Bubble Point Pressure AOP SDS HPM ADP PVT SDS HPM AOP PVT SDS HPM Trendline Psat Trendline ADP Trendline AOP 4 SPE 166097 The various mixtures of oil were flashed to standard conditions and the STO s Refractive Indices RI were measured The results are listed in Tables 6 and 7 This data can possibly be applied with the ASIST method for asphaltene analysis 4 An attempt was made to experimentally determine the minimum miscibility pressure MMP The MMP was not reached at the maximum operation pressure of 69 MPa The runs at 94 C were conducted at 45 55 and 68 4 MPa with oil recoveries of 70 75 5 and 83 2 respectively as can be seen from Table 8 Figure 5 illustrates the slim tube results and an extrapolation line is added to the data indicating that the MMP is significantly higher The indications are that the MMP value may be above 94 MPa This value is almost twice the value that may be obtained from correlations in the literature 10 13 Fig 3 CME result at 94 C for reservoir fluid with varying nitrogen concentrations Fig 4 Oil viscosity at 94 C for reservoir fluid with varying nitrogen concentrations SPE 166097 5 Fig 5 Slim tube oil recoveries with N2 injection at 94 C Data Evaluation The compositions from the TBP distillation and gas chromatography GC were compared Figure 6 demonstrates that the GC data differs from the TBP distillation data The C30 weight found in two TBP tests agrees well with each other However C30 weight from GC analysis is 35 61 while the average C30 weight from TBP analyses is 40 42 The GC and TBP distillation are two different processes for compositional analyses and both methods have some limitations The TBP analysis result is influenced by the carry over of components from one carbon number range to another range temperature control and losses especially light ends The GC analysis results are influenced by the sample preparation issues GC procedure and possible loss of heavy ends in the GC column Moreover the mol results are found from the weight composition using published default molecular weights 16 Application of correct molecular weights for individual fractions in the characterization of models is essential when establishing the fluid s molar composition Weight results are actual raw data from TBP and GC analyses and they should be used as such in tandem with correct molecular weights for the fluid that is being studied For modeling purpose in this work reliance was given to the TBP data The C36 molecular weight from TBP was 833 7 Figure 7 shows two extrapolated molecular weight curves representing C36 molecular weights of 833 7 and 725 The later of these values seem to coincide better with the C7 C35 trend A C36 molecular weight of 808 was used in establishing the models based on adjustment for a gas oil ratio of 102 2 Scm3 Scm3 and a STO density of 0 88 g cm3 The reservoir fluid composition when recombining GC analysis and TBP analysis is shown in Table 9 Fig 6 Boiling point data for stabilized oil Fig 7 Extrapolated C36 molar distribution assuming C36 molecular weights of 833 7 and 725 Phase Behavior Modeling One of the objectives of the experimental program was to establish EoS models describing the experimental data This would be a requirement to perform compositional reservoir simulation studies of the impact of gas injection Three EoS models have been established based on the measured data 6 SPE 166097 22 component PC SAFT Model15 22 component SRK Peneloux EoS Model14 17 Nine component SRK Peneloux EoS Model The PC SAFT EoS model parameters were found using the characterization procedure presented by Pedersen et al 18 The characterization procedure of Pedersen et al 19 was used to find the SRK model parameters and the associated volume corrections The model parameters are listed in Tables 10 11 and 12 The last component in each of these models represents the asphaltene components which are assumed to be in the C50 aromatic fraction 20 Figure 8 illustrates how well the EoS models reproduce the p x phase envelope data As may be seen the saturation pressure and AOP are represented fairly well However the simulated ADP s are higher than the measured values The ADP is primarily determined by the gas concentration in the liquid phase Asphaltenes will redissolve when the gas concentration is below a limiting value which is almost constant with pressure The data suggests that the gas concentration in the liquid phase at the ADP should be lower when more N2 was added to the total mixture The reason is rather that there is more asphaltene to redissolve when higher N2 amounts were added i e the low ADP s seen when more N2 is added may be due to kinetic effects and simply show that the asphaltene may require longer time to redissolve in the oil than the two hours allocated in the experimental procedure a 22 Comp PC SAFT EoS b 22 Comp SRK P EoS c 9 Comp SRK P EoS Fig 8 Experimental and simulated phase envelopes for reservoir fluid swelled with N2 at 94 C Figure 9 shows experimental and simulated CME density data for the fluid mixtures M0 M1 M2 and M3 using the 22 component PC SAFT and SRK Peneloux models The oil density of the reservoir fluid is matched very well while the simulated densities are up to 1 5 higher than the experimental values for the mixtures with nitrogen Figure 10 shows experimental and simulated oil compressibilities Figure 10a is for the reservoir fluid for which the SRK equation provides a better match at the higher pressures while the PC SAFT performs better at the lower pressures As the nitrogen content is increased the PC SAFT model becomes superior to SRK at all pressures The compressibilities may play an important role when evaluating gas injection A more compressible fluid will keep the pressure higher when the field is produced than a less compressible fluid Since three phases are present between the saturation pressure and the ADP the CME simulations were carried out using a multiflash algorithm21 22 and the simulated oil densities and compressibilities are weighted averages between the oil and the asphaltene phases Figure 11 shows experimental and simulated Y factors The Y factor is defined as 1 1 sat tot sat sat sattot sat V V p p V VV p pp factorY 1 and experimentally determined from the absolute measured volumes Near the saturation point the measured volumes of the disappearing phase are small and this may partly explain the deviations seen between the simulated and experimental Y factors SPE 166097 7 a Recombined oil M0 b Fluid mixture M1 c Fluid mixture M2 d Fluid mixture M3 Fig 9 Experimental and simulated CME oil densities at 94 C with 22 component PC SAFT and SRK EoS a Recombined oil M0 b Fluid mixture M1 c Fluid mixture M2 d Fluid mixture M3 Fig 10 Experimental and simulated CME oil compressibilities at 94 C with 22 component PC SAFT and SRK EoS 8 SPE 166097 a Recombined oil M0 b Fluid mixture M1 c Fluid mixture M2 d Fluid mixture M3 Fig 11