Low-salinity water injection for EOR applications and for shale and tight sand fracturing has become a widely accepted approach. Experimental and modeling work is slowly unraveling the complexity of this system, with no unified theory to explain the fundamentals behind it. Our work adds a new spin to the topic, where the non-monotonic impact of salinity on contact angle reported in literature is linked to its non-monotonic impact on the properties of the water-oil interface.
We used a crude oil sample that originated from a field in Texas to create surfactant-stabilized brine-in-oil emulsions. We synthesized different brine systems starting from deionized water using two different salts, NaCl and CaCl2 at 8.55, 85.5 and 855 mMol/L. We quantified the stability of the emulsion using both gravimetric and centrifuge methods. We measured the variation in the viscosity of the emulsion for different brine fractions from 10 to 50 wt%.
The results show a different effect of salt on stability for different values of water-cut. This effect can range from a stability being directly proportional to salt concentration in one case, to being inversely proportional to salt concentration in the other case, including a scenario where a non-monotonic impact is recorded.
The work provides a comprehensive and detailed set of experiments on various measurements relating to the brine-oil interactions away from the influence of rock minerals. It shows similar trends to what is reported in the literature on experiments and simulations where carbonate and sandstone rock minerals are included. This brings to question some of the theories that are used to explain this behavior given that the complexity is evident even without the rock presence.
The pressure response observed during the unsteady state displacement is a critical factor in determining the steady value and contains valuable characteristics about the rock permeability and capillary pressure. Our objective is to elucidate the mechanism of the unsteady state displcment and its impact on the pressure reponse. We tried to match the experimentally-measured pressure profile using both numerical simulation and analytical solutions. Promising results are observed when the capillary pressure is considered. The results clarify that this response is not a function of gas compressibility or viscous fingering, but is directly linked to the ratio of liquid fractional flow to liquid relative permeability as a function of saturation. The relative permeability exponents have a direct role to play in this regard. This work highlights the inacpaibility observed in a reservoir simulator to capture the pressure signature. This brings into question the ability of such simulators to provide reliable data when it comes to model the displacement processes at the core-scale.
Accurate determination of the dew point pressure of gas condensates in nano-porous ultra-low permeability reservoirs is crucial to prevent liquid dropout inside the formation. This paper presents a proof of concept experimental data and procedure to explain the effect of the pore size distribution on the degree and direction of the shift in the saturation pressure of gas mixtures under confinement compared to the bulk behavior.
We built a packed bed of BaTiO3 nanoparticles, providing a homogenous porous medium with pores of 5 to 50 nm, providing a volume more than 1000 times larger than typical nano channels. We designed an isochoric apparatus to monitor pressure for a fixed volume of fluid under confinement and bulk conditions simultaneously. A binary mixture of ethane-pentane undergoes an isochoric process with pressures of 10 to 1500 psi and temperatures of 290 to 425 K. The result is a set of Isochoric lines for the bulk and confined sample, plotted on the phase envelope to demonstrate the change in saturation pressure.
Many attempts in explaining the shift in saturation pressures of the reservoir fluid confined in the narrow pores of unconventional reservoirs compared to those of the bulk can be found in the literature. However, there are some contradiction between the predicted behavior using different mathematical approaches. Experimental data could be substantially helpful in both validating models and improving the understanding of the fluid behavior in these formations. Contrary to what many published models predict, our results show that confinement effects shift the dew point pressure towards higher values compared to the bulk for a fixed temperature in the retrograde region. In the non-retrograde region, however, this shift is towards lower dew point pressure values for the confined fluid compared to the bulk. Capillary condensation is assumed to be the main source of the deviations observed in the behavior of fluids inside nanopores. We evaluate published models, including those based on EOS modifications, by comparing it to experimental results to provide a quantification of their accuracy in predicting saturation pressure values for confined mixture.
This paper provides an alternative approach to examine the effect of pore size on phase behavior over a decent and practical range of pressures and temperatures. The synthesized porous medium is very helpful in uncoupling the effect of pore size from the effect of mineralogy on the observed deviations in behavior. Experimental findings are valuable for validating existing theories and can be used to adjust proposed mathematical approaches towards better predictions of saturation pressures for other systems.
Propped hydraulic fractures have enabled economic hydrocarbon production from organic rich shales. Laboratory testing of proppants can help in systematic evaluation of different factors that can affect proppant performance. This study is focused on long-term conductivity measurements of proppant-packs at simulated reservoir pressure and temperature conditions. Mechanisms like proppant crushing, embedment, and diagenesis are investigated.
Testing was done using a conductivity cell made of Hastelloy; allowing simultaneous measurement of fracture compaction and permeability. The proppant filled fracture (concentration: 0.75-3 lb/ft2) is subjected to axial load (5000 psi) to simulate closure stress. Brine is flowed through the pack at a constant rate (3 ml/min) at elevated temperature (250° F) over an extended duration of time (from 10-60 days). 20/40 and 60/100 mesh Ottawa sand were used in this study. The proppant-pack performance is evaluated between shale platens fabricated from Eagle Ford rock (58% clay by wt.; Nanoindentation Young's modulus - 16 GPa).
Experiments on the 20/40 and 60/100 Ottawa sand (1.5 lb/ft2 proppant concentration) at elevated pressure (5000 psi) and temperature (250° F), spanning 10 days demonstrate that proppant size strongly impacts proppant performance. The proppant-pack permeability for 60/100 sand drops dramatically within a few hours. The 20/40 proppant permeability is double the permeability of 60/100 sand even after 10 days of testing. Approximately 60% compaction is observed over the test duration, with 28% contribution from proppant crushing and rearrangement, and 32% contribution from embedment. Particle size analysis of proppant grains and SEM images verify proppant crushing, fines migration and embedment as dominant damage mechanisms. Proppant embedment and crushing are observed to be dependent on the shales being tested.
Fracturing jobs involve maintaining a basic pH environment for optimal performance of fluid additives for better proppant placement via control on viscosity. A second study was conducted to compare performance on similar Eagle Ford shale by altering the fluid chemistry (pH ~ 10.5) to understand the impact on permeability and compaction over time. Over a duration of 20 days, the permeability dropped from 120 darcy to 200 md. After 8 days, the pH:10 brine permeability was 10 times lower than pH:7 brine permeability. After 18 days, the fracture width reduced by 90%, indicating a creep behavior. High silica content (>20 ppm) was observed in the outlet brine. The proppant and rock surface were studied under SEM to investigate the role of secondary mineral growth during the drastic reduction of permeability.
This study is focused on understanding fracture conductivity under as realistic near
Data mining has become increasingly crucial in deciphering reservoir dynamics given that operators currently acquire an enormous amount of data. These data contain valuable information about subsurface processes. Interwell connectivity is one of the most significant aspects of subsurface characterization that can impact a project's success. In this study, we present novel techniques to quantify and monitor interwell communication by applying signal processing methods to observed and derived well-based measurements.
We construct a suite of realistic reservoir models under varying conditions involving multiple producing and water injection wells. More than 40 static and dynamic parameters including permeability, porosity, water saturation, fluid properties and rock-fluid interaction terms are varied using experimental designs to capture realistic uncertainty. Waterflood scenarios are modeled using streamline simulation to infer injector-producer pair connectivity, pattern allocations, drainage efficiency, and their evolution period. These injector-producer variables are analyzed using numerous signal processing methods including cross-correlation, time-lag correlation coefficient, coherence, and periodogram, among others. Well variables examined involve pressure, rate, and their derivative functions.
We employed a thorough and systematic multipronged approach to decipher signal processing of the injector-producer well variables. At one level, the objective was to identify which variables pair provides meaningful connectivity information. Combination of well variables examined includes injector bottomhole pressure (BHP) - producer BHP; injection rates - production rates; injector productivity index (PI) - producer PI; injector well variables - producer gas-oil ratio; and
The other objective was to identify which signal processing technique(s) will be most useful to infer interwell connectivity. To verify well connectivity, we used streamline simulation allocation pair-wise values. Our analyses indicate cross-correlation of
We examined and devised several signal-processing techniques of well variables to assess interwell connectivity in realistic reservoir settings. The approaches reveal new insights into determining reservoir communication metrics. The proposed methods can be easily implemented in the automated virtual flowmetering system. These methods also help identify the predominant injector-producer pairs and making operational decisions at any stage of any waterflood and enhanced recovery projects.
This paper examines the utilization of small-scale gas to liquid (GTL) plants for the production of transport fuels using abundant gas production from shale plays in the U.S. It is well-documented that GTL technology can be successfully implemented to convert natural gas to transport fuels. However, our literature is lacking an economic feasibility study of utilizing small-scale GTL plants as an additional stream of income for shale gas producers. This paper describes two different practical cases detailing field constraints a shale gas producer should overcome to successfully generate additional income through GTL technology in a reasonable time frame. Economic metrics such as Net Present Value (NPV), Internal Rate of Return (IRR), Cost-to-Profit ratio and Payback Period were used to assess the success of GTL technology at each given business case. For strategic decision making, sensitivity was built into the market drivers such as CAPEX, OPEX, interest rate, efficiency feedstock price, etc., and their level of influence on each economic performance benchmarks were analyzed. Monte Carlo simulation was used to carry out sensitivity analysis in each case to assess the mean and standard deviation of each economic performance metric when the range of possible values of the market drivers were put into consideration. It is expected that the outcome of this research would guide shale gas producers and private investors when considering a GTL investment to monetize their assets in the United States and beyond.
This study presents a novel method to estimated pore volume compressibility of shale samples based on mercury injection test data. We revisit our previous study (SPE-185059-PA) for more realistic estimation of pore volume compressibility for shale samples. We present a mathematical model to determine accessible porosity and pore compressibility as a function of pressure using Mercury Injection Capillary Pressure (MICP) data.
During MICP testing in a typical shale sample, the rock sample experiences conformance, compression, and intrusion stages as effective pressure increases. By evaluating compression stage, we calculate bulk compressibility. Further by introducing a system of equations, bulk compressibility is decomposed to estimate accessible pore and grain compressibility separately. Different from our previous model, in this study grain compressibility is calculated based on weight average of mineralogy determined from Fourier-transform infrared spectroscopy (FTIR) experiments. Moreover, bulk compressibility obtained from MICP data is compared with the values calculated from ultrasonic velocity measurements. Samples from both Haynesville shale plays are used to perform our study and validate the hypothesis.
Our results indicate that pore compressibility values are higher than anticipated, where calculated values are in the range of 1E-5 1/psi for shale samples at lower pressure. When pressure reaches to 8000 psi, pore compressibility reduces to the range of 1E-6 1/psi in most of the cases. Moreover, when compared with ultrasonic velocity measurements, results indicate that bulk compressibility obtained from MICP is overestimated at lower pressures and slightly underestimated at higher pressures.
The outcome of the paper changes the industry's take on prediction of the reservoir performance, especially the rock compaction mechanism. This study suggests that production owing to rock compaction can be much greater than what has often regarded, which can change the performance evaluation on a great number of reservoirs in terms of economic feasibility.
Patel, Harshkumar (University of Oklahoma) | Hariharan, Hari (Shell International Exploration & Production Inc.) | Bailey, Greg (Shell International Exploration & Production Inc.) | Jung, Gonghyun (Shell Global Solutions US Inc.)
API flanges maintain integrity through metal-to-metal seal between gasket and flange groove, where sealability depends on contact stresses through bolt makeup-load, tension, fluid-pressure, bending moment. Approaches like API-6AF2 have limitations. With increased deep-water operations, there is an urgent need to understand true sealability/leakage. This requires micro-scale examination of seal. Very few FEA in literature model surface conditions. The objective here has been to develop an analytical model to estimate contact stresses and leakage considering surface topography.
This work presents a novel approach for modelling sealability/leakage in metal-to-metal surfaces. It utilizes a contact-mechanics and a fluid-flow model. Deterministic multi-asperity contact-mechanics model provides quantitative estimation of gasket contact stresses, contact gap, and contact area. The leakage model uses contact gap information and correlates it with hydraulic permeability between gasket and groove surfaces and predicts leakage using fluid flow through porous media equations. User inputs are gasket surface topography, size, material properties, operating pressure, and fluid viscosity. The calculations are performed on a small surface domain and results are then scaled-up to obtain contact load/leakage for the entire flange/gasket.
Various types of artificially generated surfaces were considered in the model and a parametric study was conducted. Effects of surface finishing have been explained by visual representation of model outputs such as contact status, load distribution, and leakage path. It was observed that critical contact stress to achieve complete sealability is highly dependent on surface characteristics. For similar surface topography, leakage rates are primarily a function of surface RMS. For the same RMS, it is more difficult to seal a randomly rough surface than a patterned or uniform one. As expected, it is easier to seal a soft gasket than a harder one. Similarly, it becomes progressively difficult to seal larger flanges.
Parametric studies/analysis can help improve understanding of leakage. The models can be used to understand relative magnitude of challenges in sealing gases/liquids at true viscosities. With further refinement and experimental validation, the models could serve as a design tool that could greatly assist in selecting effective seal and improve well process safety. Further, the presented approach can also be applied to develop leakage models for other metal-to-metal seal applications such as tubular connections, expandables, etc.
Compressional and shear travel time logs (DTC and DTS) acquired using sonic logging tools are crucial for subsurface geomechanical characterization. In this study, 13 ‘easy-to-acquire’ conventional logs were processed using 6 shallow learning models, namely ordinary least squares (OLS), partial least squares (PLS), elastic net (EN), LASSO, multivariate adaptive regression splines (MARS), and artificial neural network (ANN), to successfully synthesize DTC and DTS logs. Among the 6 models, ANN outperforms other models with R2 of 0.87 and 0.85 for the syntheses of DTC and DTS logs, respectively. The 6 shallow learning models are trained and tested with 8481 data points acquired from a 4240-feet depth interval of a shale reservoir in Well 1, and the trained models are deployed in Well 2 for purposes of blind testing against 2920 data points from 1460-feet depth interval. Following that, 5 clustering algorithms are applied on the 13 ‘easy-to-acquire’ logs to identify clusters and compare them with the prediction performance of the shallow learning models used for log synthesis. Dimensionality reduction algorithm is used to visualize the characteristics of the clustering algorithm. Hierarchical clustering, DBSCAN, and self-organizing map (SOM) algorithms are sensitive to outliers and did not effectively differentiate the input data into consistent clusters. Gaussian mixture model can well differentiate the various formations, but the clusters do not have a strong correlation with the prediction performance of the log-synthesis models. Clusters identified using K-means method have a strong correlation with the prediction performance of the shallow learning models. By combining the predictive shallow learning models for log synthesis with the K-means clustering algorithm, we propose a reliable workflow that can synthesize the DTC and DTS logs, as well as generate a reliability indicator for the predicted logs to help an user better understand the performance of the shallow learning models during deployment.
The single-well chemical-tracer test (SWCTT) has been applied for decades with much success in estimating residual oil saturation in near-wellbore locations. The information obtained from an SWCTT is critical for designing a method for enhanced oil recovery (EOR). However, a key assumption in the conventional SWCTT is that only single-phase (water) is mobile. In reality, this is often not the case, and significant error can occur if the conventional SWCTT analysis method is used when multiple phases flow at the same time. The objective of this study is to improve the accuracy and precision of SWCTT interpretation in a multiphase-flow condition.
In this paper, we propose an innovative procedure of SWCTT and modify the method of moment (MOM), aiming at the two-mobile- phase condition. In the development of the algorithm, a ratio parameter is introduced to adjust the calculated swept-volume difference between the conservative tracer and the partitioning tracer. In addition, a mixture injection of oil and water is required, instead of the pure-water injection in an SWCTT.
The proposed approach is verified through numerical simulation on synthetic cases with known input parameters. The model being simulated consists of a radial-flow regime with a single vertical well in the center. The input oil saturation varies from 0.1 (immobile oil saturation) to 0.9. Our results show that the saturation estimated from the modified MOM matched the simulation input data, indicating that our approach is able to capture the saturations under two-mobile-phase condition. Moreover, the modified MOM can also be applied in single-mobile-phase condition and can improve the accuracy of conventional MOM.