Wang, Xin (Rice University) | Ko, Saebom (Rice University) | Liu, Ya (Rice University) | Lu, AlexYi-Tsung (Rice University) | Zhao, Yue (Rice University) | Harouaka, Khadouja (Rice University) | Deng, Guannan (Rice University) | Paudyal, Samridhdi (Rice University) | Dai, Chong (Rice University) | Kan, Amy T. (Rice University) | Tomson, Mason B. (Rice University)
Iron sulfide scaling is a severe problem in flow assurance and asset integrity in oil and gas and deep-water production. FeS scale control is challenging due to the extremely low solubility, fast precipitation kinetics and complexity of ferrous iron and sulfide chemistry. Despite the ubiquity of FeS, we have limited understanding about the kinetics and thermodynamics of iron sulfide. To address this problem, we have developed a reliable anoxic plug flow reactor using argon gas to remove oxygen and PIPEs or MES buffer to control pH. The FeS (mackinawite) solubility, precipitation kinetics and phase transformation were the focus of this study. The impact of temperature (25 – 90°C), pH (5.92 – 6.91), ionic strength (0.15 – 4.30 M), Fe(II) to S(-II) ratio, dispersant and chelating reagent have been investigated. It was found that mackinawite is always the first FeS precipitated and could be stable for a week. It was suggested that low pH, high temperature and low ionic strength could accelerate the FeS phase transformation. FeS precipitation is under diffusion control at pH lower than 6.1, which could be accelerated by high temperature and high ionic strength. But the precipitation kinetics would be faster at higher pH. Some evidence suggests the importance of neutral FeS(aq) species at pH 6 −7. A polymeric compound containing amide functional group showed a promising effect by controlling the FeS particle size and reducing FeS scale retention rate. EDTA showed satisfactory FeS scale inhibition effect, as well as reducing FeS scale retention and H2S corrosion rate.
Zhao, Yue (Rice University) | M. Sriyarathne, H. Dushanee (Rice University) | Harouaka, Khadouja (Rice University) | Paudyal, Samridhdi (Rice University) | Ko, Saebom (Rice University) | Dai, Chong (Rice University) | Lu, Alex Yi-Tsung (Rice University) | Deng, Guannan (Rice University) | Wang, Xin (Rice University) | Kan, Amy T (Rice University) | Tomson, Mason (Rice University)
Silica is ubiquitous in oil and gas production water because of quartz and clay dissolution from rock formations. Furthermore, the produced water from unconventional production often contains high Ca2+, Mg2+ and Fe2+ concentrations. These common cations, especially iron, can form aqueous or surface complexes with silica and affect the nucleation inhibition of other scales such as barite. Thus, it is important to investigate the silica matrix ion effects on barite scale inhibitors efficiency to evaluate inhibitor compatibility with silica and common cations in produced waters.
In this study, experimental conditions were varied from 50 mg/L to 160 mg/L SiO2 in the presence of Ca2+ (1,000 and 16,000 mg/L), Mg2+ (2,000 mg/L) and Fe2+ (10 mg/L) at 70°C and neutral pH conditions, all with a background of 1 M NaCl. Our laser scattering apparatus was used to study the effect of silica matrix ions on barite nucleation inhibition [
Thiele, Christopher (Rice University) | Araya-Polo, Mauricio (Shell International Exploration & Production, Inc.) | Alpak, Faruk Omer (Shell International Exploration & Production, Inc.) | Riviere, Beatrice (Rice University)
Direct numerical simulation of multiphase pore-scale flow is a computationally demanding task with strong requirements on time-to-solution for the prediction of relative permeabilities. In this paper, we describe the hybrid-parallel implementation of a two-phase two-component incompressible flow simulator using MPI, OpenMP, and general-purpose graphics processing units (GPUs), and we analyze its computational performance. In particular, we evaluate the parallel performance of GPU-based iterative linear solvers for this application, and we compare them to CPUbased implementations of the same solver algorithms. Simulations on real-life Berea sandstone micro-CT images are used to assess the strong scalability and computational performance of the different solver implementations and their effect on time-to-solution. Additionally, we use a Poisson problem to further characterize achievable strong and weak scalability of the GPU-based solvers in reproducible experiments. Our experiments show that GPU-based iterative solvers can greatly reduce time-to-solution in complex pore-scale simulations. On the other hand, strong scalability is currently limited by the unbalanced computing capacities of the host and the GPUs. The experiments with the Poisson problem indicate that GPU-based iterative solvers are efficient when weak scalability is desired. Our findings show that proper utilization of GPUs can help to make our two-phase pore-scale flow simulation computationally feasible in existing workflows.
A discontinuous Galerkin method of first order is proposed to solve the three-phase flow problem in three-dimensional heterogeneous reservoirs. The formulation is based on the compositional model and the primary unknowns are the total mass fraction of gas, the aqueous phase saturation and the liquid phase pressure. The algorithm is sequential and controls the nonlinearity with a subiteration scheme. Robustness of the method is shown on reservoirs with different heterogeneities: random permeability field, reservoir with barriers and layered reservoir. The algorithm easily handles phase appearance and disappearance, as well as mass transfer between the vapor and liquid phase.
Although iron sulphide (FeS) scale is not as common as carbonate and sulfate scales, it is difficult to inhibit, especially at high temperature conditions, due to its low solubility and fast precipitation kinetics. Moreover, the complexity of FeS solution and solid phase chemistry makes FeS deposition and related issues difficult to be solved. This study is to identify more efficient and effective dispersants and inhibitors for FeS scale. Polyacrylamide (PAM), polyvinyl pyrrolidone (PVP), polyoxazoline (OX) and carboxymethyl cellulose (CMC), which are frequently employed during oil and gas production activities for various purposes, successfully prevented FeS particles from settling. CMC was the most effective to disperse FeS particles in brines and it can disperse FeS particles under the conditions of as high as 4M of ionic strength. The size of FeS stabilized with polymers remained in nano-scale. Polymers did not work as threshold inhibitors, but prevented particle growth. Phosphonates and carboxylate chelating agents were also tested for FeS scale inhibition. Diethylenetriamine pentamethylene phosphonate (DTPMP), ethylenediaminetetraacetate (EDTA) and nitrilotriacetate (NTA) successfully inhibited FeS nucleation greater than 90% in a given reaction time of 2 hours at 70 °C, based on the measurement of Fe concentration in filtered solution with 0.22 μm syringe membrane. NTA showed the best inhibition performance at pH 5.0 and all three inhibitors stopped FeS nucleation at a substoichiometric concentration of inhibitors to iron(II). EDTA performed better than NTA and DTPMP at pH 6.7 at about 10% excess of EDTA molar concentration over iron(II). As pH and saturation index (SI) increased, greater concentrations of inhibitors were required to inhibit FeS scale.
Agent-based models (ABMs) provide a fast alternative to traditional partial differential equation (PDE)- based oil reservoir models by applying localized inexpensive simulations, rather than solving a partial differential equation at every time-step. However, while there have been theoretical and numerical results obtained with ABMs in social science applications, the accuracy of ABMs has not been analyzed in the context of oil reservoir modeling.
In this work a new laser-hydrothermal apparatus is designed to evaluate nucleation of scale minerals at temperature up to 250°C, its reliability is proven by measuring induction time data of barite from 90°C to 250°C at various Saturation index (SI) values, with the objective that such a design would contribute to the scale-related research at extreme temperature.
Background solution (e.g. 1m NaCl) in a borosilicate glass bottle was placed inside a hydrothermal reactor. GC oven was used for temperature control and a modified Nd-Fe-B magnetic stirrer under the oven was used for stirring. A PFA tubing was selected to be the part with contact with solution for corrosion control. Using a 0.5 ml sample loop in two separate 6-ways switch valves, Ba2+ and SO42-concentrated solutions were simultaneously injected into a background solution. After supersaturation was initiated, a laser beam penetrated through the sight glasses installed on the both sides of the reactor to record the turbidity change during the nucleation process.
Induction time (tind) of Saturation index (SI) values from 0.34 to 1.02 was measured at temperatures from 90°C to 250°C. Data correlates well with data from previous laser test at 90°C in a regular beaker experiment. The induction time (tind), that is, how fast a supersaturated solution induces nucleation and crystal growth to form detectable turbidity, decrease with temperature at a fixed SI value. For example, tind of 93 minutes at 150°C decreases to about 2 minutes at 250°C under the the same SI value of 0.65, indicating that increasing temperature facilitates the nucleation process at certain supersaturation levels. This temperature impact can be attributed both by thermodynamics and kinectic aspects.
Nuclear magnetic resonance (NMR) T2 spin-spin relaxation is a well-established technique in petrophysics labs for quantifying bound/free water and pore-size distribution of reservoir rocks. The method has also been used to measure oil and water saturations, and to characterize wettability alterations for oil/water/rock systems. The T2 relaxation distribution measured by hydrogen NMR is the sum of contributions from both oil and water in the core. It is therefore necessary to separate the T2 signals of oil from water. Since deuterium oxide (D2O) does not have a NMR signal at the resonance frequency for hydrogen, brine made with D2O is commonly used as the aqueous phase to determine the oil saturation from NMR.
The objective of this work was twofold: (1) to validate the oil saturations in the core with NMR T2 relaxation at connate water saturation (before and after aging) and residual oil saturation after waterflooding; and (2) to investigate the potential hydrogen-deuterium (H-D) ion exchange between rock minerals and D2O. Berea sandstone cores were used along with the crude oil from one of the fields in the Sarawak Basin, Malaysia. The aqueous phase was a synthetic brine made with either deionized water or D2O.
Two cores containing the crude oil with D2O brine as the connate (or initial) water were aged at 75eC for up to 65 days. During the aging period, the cores were scanned three times for T2 measurements. The measured T2 volumes (supposedly a measure of the oil volume) of the two cores kept increasing as the aging time increased. However, mass balance indicated that the oil saturation was the same before and after aging. The inconsistent oil saturation measured by NMR indicated that there was H-D ion exchange between the rock minerals and D2O. The cores were then flooded with the fresh D2O brine, after which the residual oil from NMR agreed with that from mass balance, indicating that the fresh D2O had replaced the connate D2O brine affected by H-D ion exchange.
Additionally, two cores fully saturated with D2O brine were also measured by NMR before and after aging at 75°C, again confirming the H-D ion exchange between the rock minerals and D2O. Finally, the mixture of the crude oil and D2O was measured by NMR before and after aging at 75°C, indicating that the interactions between the crude oil and D2O increased the T2 relaxation time. The total T2 volume was not affected.
This work provides evidence of H-D ion exchange between rock minerals and D2O at elevated temperature. It is recommended that such interactions between the rock minerals and D2O brine be considered for related tests, especially when elevated temperature is involved.
Kan, Amy T. (Rice University) | Dai, Joey (Zhaoyi) (Rice University) | Deng, Guannan (Rice University) | Harouaka, Khadouja (Rice University) | Lu, Yi-Tseng (Rice University) | Wang, Xin (Rice University) | Zhao, Yue (Rice University) | Tomson, Mason B. (Rice University)
Numerous saturation indices and computer algorithms have been developed to determine whether, when, and where scale will form. However, scale prediction can still be challenging because the predictions from different models often differ significantly at extreme conditions. Furthermore, there is a great need to accurately interpret the partitioning of water (H2O), carbon dioxide (CO2), and hydrogen sulfide (H2S) between different phases, as well as the speciations of CO2 and H2S. This paper summarizes current developments in the equation-of-state (EOS) and Pitzer models to accurately model the partitioning of H2O, CO2, and H2S in hydrocarbon/aqueous phases and the aqueous ion activities at ultrahigh-temperature, ultrahigh-pressure, and mixed-electrolytes conditions. The equations derived from the Pitzer ion-interaction theory have been parameterized by regression of more than 10,000 experimental data from publications over the last 170-plus years using a genetic algorithm on the supercomputer DAVinCI at Rice University. With this new model, the 95% confidence intervals of the estimation errors for solution density are within 4×10–4 g/cm3. The solubility predictions of CO2 and H2S are accurate to within 4%. The saturation-index (SI) mean values for calcite (CaCO3), barite (BaSO4), gypsum (CaSO4·2H2O), anhydrite (CaSO4), and celestite (SrSO4) are accurate to within ±0.1—and for halite the values are within ±0.01—most of which are within experimental uncertainties. This model accurately defines the pH value of the production tubing at various temperature and pressure regimes and the risk of H2S exposure and corrosion. Furthermore, our model is able to predict the density of soluble chloride and sulfate SO2–4 salt solutions within ±0.1% relative error. The ability to accurately predict the density of a given solution at temperature and pressure allows one to deduce when freshwater breakthrough will occur. In addition, accurate predictions can only be reliable with accurate data input. The need to improve the accuracy of scale prediction with quality data will also be discussed.
Wave-equation migration velocity analysis (WEMVA) is a method that can provide low-frequency, long-wavelength velocity models. The presence of low-frequency information is critical to avoid cycle-skipping in iterative inversions such as full-waveform inversion (FWI). Such information can be used in an inversion to obtain an estimate of the subsurface velocities and improve subsurface imaging. WEMVA uses a tomographic operator to produce these model updates, which is both computationally intensive to run and uses code that is not widely available. I introduce an approximation to the tomographic operator using a finite-difference scheme and reverse-time migration (RTM) that significantly reduces the cost of computation. The following examples demonstrate WEMVA in the common-offset domain calculated by using images generated by RTM in the common-offset domain.
Presentation Date: Wednesday, October 17, 2018
Start Time: 1:50:00 PM
Location: Poster Station 22
Presentation Type: Poster