Hwang, Jongsoo (The University of Texas at Austin) | Sharma, Mukul (The University of Texas at Austin) | Amaning, Kwarteng (Tullow Ghana Limited) | Singh, Arvinder (Tullow Ghana Limited) | Sathyamoorthy, Sekhar (Tullow Ghana Limited)
Understanding injectivity is a critical element to ensure that sufficient volumes of water are being injected into the reservoir to maintain reservoir pressure, to ensure good reservoir sweep and minimize well remediation. It is, however, challenging to describe the large injectivity changes that are sometimes observed in injectors operating under fracturing conditions. This study presents a field case study with the following objectives: 1) explain the complicated injectivity changes caused by fracture opening/closure with injection-rate variations, 2) define a safe operating envelope (for injection pressure and rate) that ensures fracture containment and injection into the target zone, and 3) prescribe how the injection rate should be changed to achieve higher injectivities. Injector operating conditions are developed using results from a full 3-dimensional fracture growth simulation to ensure fracture containment in a multi-layered reservoir.
We present field injectivity observations, a comprehensive simulation workflow and its results to explain injector performance in a deep-water turbidite sand reservoir with multiple splay sands. Understanding the impact on fracture propagation and containment allows us to make quantitative suggestions for the operating envelopes for long-term injection-production management. Strategies for high-rate injection to sustain the injection well performance long-term are discussed.
Simulation results show that, at injection rates over 5,000 bwpd, injection induced fractures propagate. Fracture closure induced by injection shut-down is used to compute the bottom-hole pressure decline as a function of time. The fracture opening/closure events and the thermally induced stress were the primary factors impacting injectivity. The simulation results suggested several ways to improve the injectivity while ensuring fracture containment. Injection under fracturing conditions into a single zone at a high rate is shown to be feasible and this allows us to support a substantial increase in injectivity. This must, however, be done at pressures that will not cause a breach in the bounding shales. The 3-dimensional fracture simulations identified the operating pressure and rate envelope to maximize the injection rates while minimizing the risk of breaching the cap rock and inter-zone shales.
The wettability of reservoir rocks impacts many aspects of well planning and production, from estimating hydrocarbon saturation to enhanced oil recovery. Wettability is often experimentally quantified through laboratory measurements; however, in-situ wettability assessment is challenging. In this work, we introduce a new method to quantify wettability using resistivity measurements obtained from either well logs or core measurements. The objectives of this paper are (i) to introduce a resistivity-based wettability index from our recent analytically-derived resistivity model that takes into account wettability and (ii) to verify the reliability of the new resistivity-based wettability index using Amott Index, U.S. Bureau of Mines (USBM), and/or contact angle wettability measurements as reference.
We quantify the resistivity-based wettability index using our new analytically-derived resistivity model which requires as inputs the resistivity of the rock-fluid system and brine, water saturation, porosity, and pore-geometry-related parameters. Water saturation and porosity can be estimated from the interpretation of borehole geophysical or core measurements. The pore-geometry-related parameters can be estimated from image analysis performed on three-dimensional pore-scale images (e.g. micro-computed tomography) or through a physics-based calibration method. Next, we calculate the resistivity-based wettability index by minimizing the error between the measured and predicted resistivity of the rock-fluid system. To verify this method, we prepare core samples covering a wide range of wettability states and saturation levels. We vary the wettability of the samples by injecting brine, an anionic surfactant solution, or a naphthenic acid and decane solution to make the core samples water-, mixed-, or oil-wet, respectively. Finally, we obtain the resistivity-based wettability index in the core samples and verify its reliability by comparing the estimates against the Amott Index and the contact angle measurements. We also used previously documented data in Berea sandstone for further verification of the new method.
We successfully demonstrated the reliability of the introduced resistivity-based wettability index for limestone and sandstone core samples. The resistivity-based wettability indices were in agreement with both Amott and USBM Indices for the limestone and sandstone samples, respectively. The average absolute difference between the resistivity-based wettability index and the Amott and USBM Indices was less than 0.4 for all the core samples documented in this paper. The outcomes of this work can potentially be used for assessment of wettability from borehole geophysical measurements, to deliver in-situ properties of rocks in real-time. Additionally, the new resistivity model consists only of physically meaningful parameters and minimizes calibration efforts. Furthermore, if the wettability, porosity, and pore-geometry-related parameters are known, then we can use this resistivity model to obtain water saturation without the need for calibration.
Cost-effective exploitation of heterogeneous/anisotropic reservoirs (e.g., carbonate formations) reckons on accurate description of pore structure, dynamic petrophysical properties (e.g., directional permeability, saturation-dependent capillary pressure), and fluid distribution. However, techniques for reliable quantification of permeability and hydrocarbon saturation still rely on model calibration using core measurements. Furthermore, assessment of saturation-dependent capillary pressure has been limited to experimental measurements, such as mercury injection capillary pressure (MICP). The objectives of this paper include (a) developing a new multiphysics workflow to simultaneously quantify rock fabric features (e.g., porosity, tortuosity, and effective throat size) and hydrocarbon saturation from integrated interpretation of nuclear magnetic resonance (NMR) and electric measurements, (b) introducing rock physics models that incorporate the quantified rock fabric and partial water/hydrocarbon saturation for assessment of directional permeability and saturation-dependent capillary pressure, and (c) validating the reliability of the new workflow in pore- and core-scale domains.
To achieve these objectives, we introduce a new multiphysics workflow integrating NMR and electric measurements, honoring rock fabric, and minimizing calibration efforts. We estimate water saturation from the interpretation of dielectric measurements. Next, we develop a fluid substitution algorithm to estimate the
The introduced multiphysics workflow provides accurate description of the pore structure and fluid distribution in partially water-saturated formations with complex pore structure. Moreover, this new method enables real-time well-log-based assessment of saturation-dependent capillary pressure and directional permeability (in presence of directional electrical measurements) in reservoir conditions, which was not possible before. Quantification of capillary pressure has been limited to measurements in laboratory conditions, where the differences in stress field reduce the accuracy of the estimates. We verified that the estimates of permeability, saturation-dependent capillary pressure, and throat-size distribution obtained from the application of the new workflow agreed with those experimentally determined from core samples. Finally, since the new workflow relies on fundamental rock physics principles, hydrocarbon saturation, permeability, and saturation-dependent capillary pressure can be estimated from well-logs with minimum calibration efforts, which is another unique contribution of this work.
Fiallos Torres, Mauricio Xavier (The University of Texas at Austin) | Yu, Wei (The University of Texas at Austin) | Ganjdanesh, Reza (The University of Texas at Austin) | Kerr, Erich (EP Energy) | Sepehrnoori, Kamy (The University of Texas at Austin) | Miao, Jijun (SimTech LLC) | Ambrose, Raymond (EP Energy)
Optimizing spacing of infill wells and fractures can lead to large rewards for shale field operators, and these considerations have influences on primary and tertiary development of the field. Although several studies have been employed to show the existence of well interference, few models have also implemented Huff-n-Puff and injection containment methods to optimize further hydraulic fracture designs and pressure containment to improve the efficiency of Enhanced Oil Recovery (EOR). This study has performed a rigorous workflow for estimating the impacts of spatial variations in fracture conductivity and complexity on fracture geometries of interwell interference. Furthermore, we applied a non-intrusive embedded discrete fracture model (EDFM) method in conjunction with a commercial compositional reservoir simulator to investigate the impact of well interference through connecting fractures by multi-well history matching to propose profitable opportunities for Huff-n-Puff application. First, based on a robust understanding of fracture properties, updated production data and multi-pad wellbore image logging data from Eagle Ford, the model was constructed to perform nine wells sector model history matching. Later, inter-well connecting fractures were employed for enhanced history matching where results varied significantly from unmeasured fracture sensitivities. The result is the implementation of Huff-n-Puff models that capture inter-well interference seen in the field and their affordable impact sensitivities focused on variable injection rates/locations and multi-point water injection to mimic pressure barriers. The simulation results strengthened the understanding of modeling complex fracture geometries with robust history matching and support the need to incorporate containment strategies. Moreover, the simulation outcomes show that well interference is present and reduces effectiveness of the fracture hits when connecting natural fractures. As a result of the inter-well long fractures, the bottom hole pressure behavior of the parent wells tends to equalize, and the pressure does not recover fast enough. Furthermore, the EDFM application is strongly supported by complex fracture propagation interpretation and ductility to be represented in the reservoir. Through this study, multiple containment scenarios were proposed to contain the pressure in the area of interest.
The model has become a valuable template to inform the impacts on well location and spacing, completion design, initial huff-n-puff decisions, subsequent containment strategies (e.g. to improve cycle timing and efficiency), and to expand to other areas of the field. The simulation results and understandings afforded have been applied to the field satisfactorily to support pressure containment benefits that lead to increased pressure build, reduced gas communication, reduced offset shut-in volumes, and ultimately, improvements in net utilization and capital efficiency.
Sun, Zheng (China University of Petroleum at Beijing, Texas A&M University) | Shi, Juntai (China University of Petroleum at Beijing) | Wu, Keliu (China University of Petroleum at Beijing) | Gong, Dahong (CNPC Bohai Drilling Engineering Company Limited Directional Well Technology Services Branch) | Peng, Hui (CNPC Bohai Drilling Engineering Company Limited Mud Logging 2) | Hou, Yuhua (NO.2 Logging Branch of Bohai Drilling Engineering Co., Ltd., PetroChina Group) | Ma, Hongyan (CNPC Bohai Drilling Engineering Company Limited Directional Well Technology Services Branch) | Wang, Daning (CNPC Bohai Drilling Engineering Company Limited Directional Well Technology Services Branch) | Ramachandran, Hariharan (The University of Texas at Austin) | Liu, Yisheng (China University of Petroleum at Beijing) | Liu, Wenyuan (China University of Petroleum at Beijing) | Wang, Suran (China University of Petroleum at Beijing) | Li, Xiangfang (China University of Petroleum at Beijing)
With respect to the sharp increase in population all around the world, more and more energy and fuels are expected to achieve the counterbalance between supply and demand. Deeply attracted by its considerable and prospect recovery reserve, the exploitation, development and related research contents regarding coalbed methane (CBM), i.e., one of the unconventional gas reservoirs, are currently heat and essential topics. Without any doubt, precise determination of coal permeability will dramatically contribute to the development efficiency of CBM reservoirs. It should be noted that the permeability in CBM reservoirs possesses unique heterogeneous characteristics, especially for the different permeability at directions of face cleats and butt cleats, which will inevitably result in greatly shape-change for fluid flow field and eventually the production performance. To my best knowledge, nearly all the previous methods proposed for evaluating coal permeability assume the homogeneous permeability feature in CBM reservoirs, which show fairly great discrepancy compared with that of the realistic situation. In this work, in order to address this urgent issue, a novel permeability evaluation method is developed for the first time, which is able to generate precisely heterogeneous characteristics of coal permeability based on the water production rate versus production time curve at the early production stage. First of all, considering both orthotropic heterogeneous permeability and pressure propagation behavior in CBM reservoirs, single water phase productivity equation is seriously derived. Secondly, for simply usage purpose in field application, the obtained equation is transformed through linearization treat. Finally, combining the water production performance with the linearized equation, efficient iteration calculation procedures are given to determine the heterogeneous permeability feature. Also, the skin factor of corresponding CBM well can be determined. The applicability and accuracy of the proposed method have been successfully verified through field application. In sum, the proposed method can serve as a simple as well as an accurate tool to determine the crucial heterogeneous permeability feature in CBM reservoirs. More importantly, during the determination process, the method just requires the water production performance at the early production stage, which means that the obtained permeability characteristics can be utilized to guide production strategy adjustment in the following gas production stage. As a result, the proposed method can be regarded as a necessary preparatory work before gas production takes place in CBM reservoirs, which will play a positive and active role in optimization of ultimate gas recovery and well configuration.
Geochemical scale formation and deposition in reservoir is a common problem in upstream oil and gas industry, which results in equipment corrosion, wellbore plugging, and production decline. In unconventional reservoirs, the negative effect of scale formation becomes more pronounced as it can severely damage the conductivity of hydraulic fractures. Hence, it is necessary to predict the effect of scale deposition on fracture conductivity and production performance.
In this work, an integrated reactive-transport simulator is utilized to model geochemical reactions along with transport equations in conventional and unconventional reservoirs considering the damage to the fracture and formation matrix. Hence, a compositional reservoir simulator (UTCOMP), which is integrated with IPhreeqc, is utilized to predict geochemical scale formation in formation matrix and hydraulic fractures. IPhreeqc offers extensive capabilities for modeling geochemical reactions including local thermodynamic equilibrium and kinetics. Based on the amount of scale formation, porosity, permeability, and fracture aperture are modified to determine the production loss. The results suggested that interaction of the formation water/brine and injection water/hydraulic fracturing fluid is the primary cause for scale formation. The physicochemical properties such as pressure, temperature, and
During hydraulic fracturing, precipitation of barite and dissolution of calcite are identified to be the main reactions, which occur as a result of interaction between the formation brine, formation mineral composition, and injection water/hydraulic fracturing fluid. Calcite dissolution can increase the matrix porosity and permeability while barite precipitation has an opposite effect. Therefore, the overall effect and final results depend on several parameters such as HFF composition, HFF injection rate, and formation mineral/brine. Based on the fracturing fluid composition and its invasion depth in this study, the effect of barite precipitation was dominant with negative impact on cumulative gas production. The outcome of this study is a comprehensive tool for prediction of scale deposition in the reservoir which can help operators to select optimum fracturing fluid and operating conditions.
Despite the great interest and importance of modeling hydrocarbon production from tight oil reservoirs, the thermodynamic stability of multicomponent mixtures with capillary pressure has not been studied sufficiently. This paper introduces a practical algorithm for phase stability analysis of multi-component mixtures with capillary pressure. The capillary pressure is determined from a realistic saturation-dependent function which is representative of pore size distributions as well as other petrophysical properties such as wettability and water saturation. The new stability procedure is coupled with flash calculations. Therefore, the phase saturations and compositions of the mixture are also provided in addition to the stability condition once the solution is converged. The significance and robustness of the new method is shown in several examples with realistic tight oil and gas-condensate mixtures.
Chemical enhanced oil recovery (EOR) methods have received increased attention in recent years since they have the ability to recover the capillary trapped oil. Successful chemical flooding application requires accurate numerical models and reliable forecast across multiple scales: core scale, pilot scale, and field scale. History matching and optimization are two key steps to achieve this goal.
For history matching chemical floods, we propose a general workflow for multi-stage model calibration using an Evolutionary Algorithm. A comprehensive chemical flooding simulator is used to model important physical mechanisms including phase behavior, cation exchange, chemical and polymer adsorption and capillary desaturation. First, we identify dominant reservoir and process parameters based on a sensitivity analysis. The history matching is then carried out in a stage-wise manner whereby the most dominant parameters are calibrated first and additional parameters are incorporated sequentially until a satisfactory data misfit is achieved. Next, a diverse subset of history matched models is selected for optimization using a Pareto-based multi-objective optimization approach. Based on the concept of dominance, Pareto optimal solutions are generated representing the trade-off between increasing oil recovery while improving the efficiency of chemical usage. These solutions are searched using a Non-dominated Sorting Genetic Algorithm (NSGA-II). Finally we implement a History Matching Quality Index (HMQI) with Moving Linear Regression Analysis to evaluate simulation results from history matching process. The HMQI provides normalized values for all objective functions having different magnitude and leads to a more consistent and robust approach to evaluate the updated models through model calibration.
Significant advances have been made in chemical enhanced oil recovery (EOR) in recent years including the development of hybrid methods that combine surfactants, polymers, alkali, co-solvents, gas and heat in novel ways. New and improved chemical and physical property models have been developed to more accurately simulate these processes at the field scale. We present improved models for relative permeability, capillary pressure, the effect of polymer viscoelasticity on residual oil saturation, the effect of pH on surfactant adsorption, polymer partitioning between aqueous and microemulsion phases, and the effect of co-solvent on microemulsion viscosity. Several simulations are presented to demonstrate how the models can be used to match experimental data.
Coupled reservoir flow and geomechanics has numerous important applications in the oil & gas industry, such as land subsidence, hydraulic fracturing, fault reaction and hydrocarbon recovery etc. High fidelity numerical schemes and multiphysics models must be coupled in order to simulate these processes and their interactions accurately and efficiently. Specifically, in the applications of CO2 sequestration, the effect of geomechanics on carbon storage estimation is not negligible. However, coupled flow-geomechanics simulations are very computationally expensive and most of the computational time is usually spent for geomechanics calculations. This paper investigates a three-way coupling algorithm that uses an error indicator to determine when displacement must be updated and whether fixed-stress iterative coupling technique is required. Numerical experiments with coupled nonlinear single-phase flow and linear poromechanics shows that the three-way coupling algorithm can speed up 4 times comparing to fixed-stress iterative coupling algorithm. Extensions to coupled compositional flow with poromechanics also shows a speed-up for 5 times for continuous CO2 sequestration applications and 2 times for surfactant-alternating-gas applications (SAG). The substantial speed up makes the three-way coupling algorithm of flow and geomechanics feasible in the large-scale optimizations. Based on the three-way coupling of compositional flow and geomechanics, we experimented two black box optimization algorithms, covariance-matrix adaptation evolution strategy (CMA-ES) and genetic algorithm (GA), for the optimization of well controls during SAG process to maximize CO2 storage volume. CMA-ES outperforms GA in that it is more robust, and it achieves higher objective function value in less simulation runs. The optimized SAG process achieves 27.55% more CO2 storage volume and reduces water and surfactant consumption by 54.84%.