Browsing by Subject "Reservoir characterization"
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Item Characterization and modeling of paleokarst reservoirs using multiple-point statistics on a non-gridded basis(2012-12) Erzeybek Balan, Selin; Srinivasan, Sanjay; Lake, Larry W; Bryant, Steven L; Janson, Xavier; Zahm, Christopher KPaleokarst reservoirs consist of complex cave networks, which are formed by various mechanisms and associated collapsed cave facies. Traditionally, cave structures are defined using variogram-based methods in flow models and this description does not precisely represent the reservoir geology. Algorithms based on multiple-point statistics (MPS) are widely used in modeling complex geologic structures. Statistics required for these algorithms are inferred from gridded training images. However, structures like modern cave networks are represented by point data sets. Thus, it is not practical to apply rigid and gridded templates and training images for the simulation of such features. Therefore, a quantitative algorithm to characterize and model paleokarst reservoirs based on physical and geological attributes is needed. In this study, a unique non-gridded MPS analysis and pattern simulation algorithms are developed to infer statistics from modern cave networks and simulate distribution of cave structures in paleokarst reservoirs. Non-gridded MPS technique is practical by eliminating use of grids and gridding procedure, which is challenging to apply on cave network due to its complex structure. Statistics are calculated using commonly available cave networks, which are only represented by central line coordinates sampled along the accessible cave passages. Once the statistics are calibrated, a cave network is simulated by using a pattern simulation algorithm in which the simulation is conditioned to sparse data in the form of locations with cave facies or coordinates of cave structures. To get an accurate model for the spatial extent of the cave facies, an algorithm is also developed to simulate cave zone thickness while simulating the network. The proposed techniques are first implemented to represent connectivity statistics for synthetic data sets, which are used as point-set training images and are analogous to the data typically available for a cave network. Once the applicability of the algorithms is verified, non-gridded MPS analysis and pattern simulation are conducted for the Wind Cave located in South Dakota. The developed algorithms successfully characterize and model cave networks that can only be described by point sets. Subsequently, a cave network system is simulated for the Yates Field in West Texas which is a paleokarst reservoir. Well locations with cave facies and identified cave zone thickness values are used for conditioning the pattern simulation that utilizes the MP-histograms calibrated for Wind Cave. Then, the simulated cave network is implemented into flow simulation models to understand the effects of cave structures on fluid flow. Calibration of flow model against the primary production data is attempted to demonstrate that the pattern simulation algorithm yields detailed description of spatial distribution of cave facies. Moreover, impact of accurately representing network connectivity on flow responses is explored by a water injection case. Fluid flow responses are compared for models with cave networks that are constructed by non-gridded MPS and a traditional modeling workflow using sequential indicator simulation. Applications on the Yates Field show that the cave network and corresponding cave facies are successfully modeled by using the non-gridded MPS. Detailed description of cave facies in the reservoir yields accurate flow simulation results and better future predictions.Item Characterization of Rodessa Formation Reservoir (Lower Cretaceous) in Van Field, Van Zandt County, Texas(Texas A&M University, 2004-09-30) Triyana, YanyanThe Rodessa Formation is one of the major oil and gas reservoirs in the East Texas Basin. In Van Field, the upper Rodessa Formation consists of interbedded biotic and abiotic mudstones to grainstones. The lower Rodessa is composed of interbedded sandstones, shales, and limestones called the Carlisle Member. Based on core and well log interpretation, the Rodessa Formation was deposited on a broad, restricted, shallow marine platform interpreted to be lagoonal, subtidal, and intertidal. Both Rodessa limestone and sandstone have been altered significantly by diagenetic processes that include micritization, cementation, dissolution, neomorphism and compaction. Dissolution is the main factor that resulted in enhanced porosity and permeability while cementation adversely affected porosity. Diagenesis is interpreted to have begun in the marine phreatic environment and continued through the freshwater phreatic and shallow burial environments. Two reservoir units have been identified from core and well log interpretations. The potential reservoir within the Rodessa Formation occurs in the Carlisle Member which is composed mainly of medium to coarse grained sandstone with porosities and permeabilities in ranges of 8 to 11 percent and 46 to 896 millidarcies, respectively. The water saturation analysis has also shown the reservoir to be hydrocarbon bearing, having water saturation below 46 percent.Item Characterization of the Cana-Woodford Shale using fractal-based, stochastic inversion, Canadian County, Oklahoma(2016-05) Borgman, Barry Michael; Spikes, Kyle; Sen, Mrinal K; Wilson, Clark RThe past decade has seen a surge in unconventional hydrocarbon exploration and production, driven by advances in horizontal drilling and hydraulic fracturing. Even with such advances, reliable models of the subsurface are crucial in all phases of exploitation. This study focuses on the methods used for estimation of the elastic properties (density, velocity, and impedance), which play a key role in targeting reservoir zones ideal for hydraulic fracturing. Well-log data provides high-resolution vertical measurements of elastic properties, but a relatively shallow depth of investigation imposes spatial limitations. Seismic data provides broader horizontal coverage at lower cost, but sacrifices vertical resolution. Thin beds present in many unconventional reservoirs fall below seismic resolution. In addition, the band-limited nature of seismic data results in the absence of low-frequency content of the Earth model, as well as the high-frequency content present in well logs. Seismic inversion is a process that provides estimates of elastic properties given input seismic and well data. Stochastic inversion is a method that uses well-log data as a priori information, with an added aspect of randomness. The method generates many realizations using the same input model and takes an average of those realizations. We implement two separate stochastic inversion algorithms to estimate P-impedance in the Cana-Woodford Shale in west-central Oklahoma. First, we use a fractal-based, very fast simulated annealing algorithm that exploits the fractal characteristics found in well-log data to build a prior model. The method of very fast simulated annealing optimizes our elastic model by searching for the minimum misfit between observed and synthetic seismic traces. Next, we use a principal component analysis (PCA) based stochastic inversion algorithm to invert for impedance at all traces simultaneously. Comparison of the results with traditional deterministic inversion results shows improved vertical resolution while honoring the low-frequency content of the Earth model. The PCA-based inversion results also show improved lateral continuity of the elastic profile along our 2D line. The impedance profile from the PCA-based approach provides a better representation of the vertical and horizontal variability of the reservoir, allowing for improved targeting of frackable zones.Item Interrelationships between carbonate diagenesis and fracture development : example from Monterrey Salient, Mexico and implications for hydrocarbon reservoir characterization(2012-05) Monroy Santiago, Faustino; Marrett, Randall; Laubach, Stephen E.; Fisher, William L.; Gale, Julia; Kerans, CharlesMany low matrix-porosity hydrocarbon reservoirs are productive because permeability is controlled by natural fractures. The understanding of basic fracture properties is critical in reducing geological risk and therefore reducing well costs and increasing well recovery. Unfortunately, neither geophysics nor borehole methods are, so far, accurate in the acquisition of key fracture attributes, such as density, porosity, spacing and conductivity. This study proposes a new protocol to predict key fracture characteristics of subsurface carbonate rocks and describes how using a relatively low-cost but rock-based method it is possible to obtain accurate geological information from rock samples to predict fracture attributes in nearby but unsampled areas. This methodology is based on the integration of observations of diagenetic fabrics and fracture analyses of carbonate rocks, using outcrops from the Lower Cretaceous Cupido Formation in the Monterrey Salient of the Sierra Madre Oriental, northeastern Mexico. Field observations and petrographic studies of crosscutting relations and fracture-fill mineralogy and texture distinguish six principal coupled fracturing-cementation events. Two fracture events named F1 and F2 are characterized by synkinematic calcite cement that predates D2 regional dolomitization. A third fracture event (F3) is characterized by synkinematic dolomite fill, contemporaneous with D2 dolomitization of host strata. The fourth event (F4) is characterized by synkinematic D3 baroque dolomite; this event postdates D2. The fifth fracture event (F5) is characterized by C3 synkinematic calcite, and postdates D3 dolomite. Finally, flexural slip faulting (F6) is characterized by C3t calcite, and postdates D3 dolomite. Carbon and oxygen stable isotopes were used to validate the paragenetic sequences proposed for the Cupido Formation rocks. The dolomite isotopic signatures are consistent with increasing precipitation temperatures for the various fracture cements, as is expected if fractures grew during progressive burial conditions. Three main groups of calcite cement can be differentiated isotopically. Late calcite cement may have precipitated from cool waters under shallow burial conditions, possibly during exhumation of the SMO. The development of the Structural Diagenetic Petrographic Study protocol, and its integration with geological, geophysical and engineering data, can be applied to oil fields in fractured carbonates such as those located in Mexico, to validate its applicability.Item Modeling of recovery process characterization using magnetic nanoparticles(2013-12) Rahmani, Amir Reza; Bryant, Steven L.; Huh, ChunStable dispersions of magnetic nanoparticles that are already in use in biomedicine as image-enhancing agents, also have potential use in subsurface applications. Surface-coated nanoparticles are capable of flowing through micron-size pores across long distances in a reservoir with modest retention in rock. Tracing these contrast agents using the current electromagnetic tomography technology could potentially help track the flood-front in waterflood and EOR processes and characterize the reservoir. The electromagnetic (EM) tomography used in the petroleum industry today is based on the difference between the electrical conductivity of reservoir fluids as well as other subsurface entities. The magnetic nanoparticles that are considered in this study, however, change the magnetic permeability of the flooded region, which is a novel application of the existing EM tomography technology. As the first fundamental step, the magnetic permeability change in rock due to injecting magnetic nanoparticles is quantified as a function of particle and reservoir properties. Subsequently, a new formulation is devised to compute the sensitivity of magnetic measurements to magnetic permeability perturbations. The results are then compared with the sensitivity to conductivity perturbations to identify the application space of magnetic contrast agents. Using numerical simulations, the progress of magnetic nanoparticle bank is monitored in the reservoir through time-lapse magnetic tomography measurements that are expected. Initially, simple models for displacement of injection banks are assumed and the level of complexity is gradually increased to incorporate the realities of fluid flow in the reservoir. The fluid-flow behavior of the nanoparticles is dynamically integrated with time-lapse magnetic response. Since the nanoparticles could help illuminate the flow paths, they could be used to indirectly measure reservoir heterogeneities. Therefore, numerous case studies are demonstrated where reservoir heterogeneity could potentially be inferred. Finally, fundamental pore-scale models are developed as a first step towards the multiple fluid phases extension of the EM tomography application. Using magnetic nanoparticles to improve electromagnetic tomography provides several strategic advantages. One key advantage is that the magnetic nanoparticles provide high resolution measurements at very low frequencies where the conductivity contrast is hardly detectable and casing effect is manageable. In addition, the sensitivity of magnetic measurements at the early stages of the flood is significantly improved with magnetic nanoparticles. Moreover, the vertical resolution of magnetic measurements is significantly enhanced with magnetic nanoparticles present in the vicinity of source or receiver. The fact that the progress of the magnetic slug can be detected at very early stages of the flood, that the traveling slug’s vertical boundaries can be identified at low frequencies, that the reservoir heterogeneities could potentially be characterized, and that the magnetic nanoparticles can be sensed much before the actual arrival of the slug at the observer well, provides significant value of using magnetic contrast agents for reservoir illumination.Item Novel stochastic inversion methods and workflow for reservoir characterization and monitoring(2013-12) Xue, Yang, active 2013; Sen, Mrinal K.Reservoir models are generally constructed from seismic, well logs and other related datasets using inversion methods and geostatistics. It has already been recognized by the geoscientists that such a process is prone to non-uniqueness. Practical methods for estimation of uncertainty still remain elusive. In my dissertation, I propose two new methods to estimate uncertainty in reservoir models from seismic, well logs and well production data. The first part of my research is aimed at estimating reservoir impedance models and their uncertainties from seismic data and well logs. This constitutes an inverse problem, and we recognize that multiple models can fit the measurements. A deterministic inversion based on minimization of the error between the observation and forward modeling only provides one of the best-fit models, which is usually band-limited. A complete solution should include both models and their uncertainties, which requires drawing samples from the posterior distribution. A global optimization method called very fast simulated annealing (VFSA) is commonly used to approximate posterior distribution with fast convergence. Here I address some of the limitations of VFSA by developing a new stochastic inference method, named Greedy Annealed Importance Sampling (GAIS). GAIS combines VFSA with greedy importance sampling (GIS), which uses a greedy search in the important regions located by VFSA to attain fast convergence and provide unbiased estimation. I demonstrate the performance of GAIS on post- and pre-stack data from real fields to estimate impedance models. The results indicate that GAIS can estimate both the expectation value and the uncertainties more accurately than using VFSA alone. Furthermore, principal component analysis (PCA) as an efficient parameterization method is employed together with GAIS to improve lateral continuity by simultaneous inversion of all traces. The second part of my research involves estimation of reservoir permeability models and their uncertainties using quantitative joint inversion of dynamic measurements, including synthetic production data and time-lapse seismic related data. Impacts from different objective functions or different data sets on the model uncertainty and model predictability are investigated as well. The results demonstrate that joint inversion of production data and time-lapse seismic related data (water saturation maps here) reduces model uncertainty, improves model predictability and shows superior performance than inversion using one type of data alone.Item Proposal of a rapid model updating and feedback control scheme for polymer flooding processes(2010-05) Mantilla, Cesar A., 1976-; Srinivasan, Sanjay; Sepehrnoori, KamyThe performance of Enhanced Oil Recovery (EOR) processes is adversely affected by the heterogeneous distribution of flow properties of the rock. The effects of heterogeneity are further highlighted when the mobility ratio between the displacing and the displaced fluids is unfavorable. Polymer flooding aims to mitigate this by controlling the mobility ratio resulting in an increase in the volumetric swept efficiency. However, the design of the polymer injection process has to take into account the uncertainty due to a limited knowledge of the heterogeneous properties of the reservoir. Numerical reservoir models equipped with the most updated, yet uncertain information about the reservoir should be employed to optimize the operational settings. Consequently, the optimal settings are uncertain and should be revised as the model is updated. In this report, a feedback-control scheme is proposed with a model updating step that conditions prior reservoir models to newly obtained dynamic data, and this followed by an optimization step that adjusts well control settings to maximize (or minimize) an objective function. An illustration of the implementation of the proposed closed-loop scheme is presented through an example where the rate settings of a well affected by water coning are adjusted as the reservoir models are updated. The revised control settings yield an increase in the final value of the objective function. Finally, a fast analog of a polymer flooding displacement that traces the movement of random particles from injectors to producers following probability rules that reflect the physics of the actual displacement is presented. The algorithm was calibrated against the full-physics simulation results from UTCHEM, the compositional chemical flow simulator developed at The University of Texas at Austin. This algorithm can be used for a rapid estimation of basic responses such as breakthrough time or recovery factor and to provide a simplified characterization the reservoir heterogeneity. This report is presented to fulfill the requirements to obtain the degree of Master of Science in Engineering under fast track option. It summarizes the research proposal presented for my doctorate studies that are currently ongoing.Item Reservoir characterization of the Upper Cretaceous Woodbine Group in Northeast East Texas Field, Texas(2012-05) Dokur, Merve; Fisher, W. L. (William Lawrence), 1932-; Hentz, Tucker F.; Steel, Ronald J.East Texas field, a giant U.S. oil-field, produced 5.42 billion stock-tank barrels from discovery in 1930 through mid-2007. The lower part of the siliciclastic Upper Cretaceous Woodbine Group is reservoir rock, and almost all production comes from the upper unit, the operator-termed Main sand. The field could produce 70 million stock-tank barrels (MMSTB) using current strategies, whereas 410 MMSTB of remaining reserves from the Stringer zone (lower unit), along with bypassed pay in both units and unswept oil, is possible. These favorable statistics have increased interest in reservoir characterization of the Woodbine, especially the Stringer zone. This study delineates sandstone geometry and interprets reservoir facies and heterogeneity of the Stringer zone and Main sand in northeast East Texas field. Additional objectives are to define key chronostratigraphic surfaces, such as flooding surfaces and unconformities, and to establish a realistic depositional model for the reservoir succession. To achieve these objectives, well log analysis, core description, and net-sandstone mapping of the Stringer zone and Main sand were conducted. According to sequence-stratigraphic and depositional-system analysis, the Woodbine Group is divided into two genetically unrelated units: (1) the highstand deltaic Stringer zone and (2) the lowstand incised-valley-fill Main sand. Principal reservoir units are Stringer 1 and Stringer 2 sands within the Stringer zone and the Main sand. Stringer 2, best developed in the southwest study area, is the most promising reservoir unit for new production. Well deepening and water-flooding in this more continuous and thicker sand are proposed to increase production in East Texas field.Item Reservoir characterization using a capacitance resistance model in conjunction with geomechanical surface subsidence models(2011-12) Wang, Wenli, master of science in petroleum engineering; Patzek, Tadeusz W.; Lake, Larry W.Extraction of oil and gas can cause reduction in pore pressure, occasionally resulting in subsequent compaction that forms a surface subsidence bowl, especially in shallow reservoirs. In the last 10 years, there has been over 10 feet of subsidence in parts of the Lost Hills oil field in California (Bruno et al.,1992). The surface subsidence at Lost Hills not only causes damage to surface facilities and wells, but also reactivates faults and reduces rock permeability. Subsidence makes reservoir optimization difficult. Hence, it is important to assess or predict the surface subsidence and the reasons for subsidence early in the life of an oil field to make an optimization plan. We use jointly the capacitance resistance model (CRM) (Alberoni et al., 2002 and Yousef, et al., 2006) that relies only on injection and production data, and the InSAR satellite imagery of surface subsidence. From CRM simulations, we estimate the connectivity between injectors and producers as well as general water flow directions from individual injectors. We then superimpose well connectivity and InSAR imagery to diagnose the reasons for the subsidence. Using new surface subsidence models, which are based on the continuity equation of CRM and rock mechanics, we are able to predict the average surface subsidence at Lost Hills from the injection and production rates. Our work shows that there was significant volumetric rock damage at Lost Hills and the well connectivity changed dramatically with time because of reservoir compaction and the rock damage. We conclude that for a soft, fragile and nearly- impermeable rock such as the diatomite, high injection rate weakens the rock and creates dynamic water flow tubes or ‘channels’ without providing good pressure support to the reservoir. These high permeability ‘channels’ re-circulate most of the injected water between the injectors and producers. Our CRM/InSAR approach is new and gives insights into the time-dependent and spatially variable fluid flow fields in a relatively shallow waterflood. Consequently, we may be able to suggest optimum water injection strategies to enhance oil production, while minimizing rock damage and surface subsidence. In addition, the proposed surface subsidence models are convenient and reliable to predict the average surface subsidence.Item The sedimentology and stratigraphy of the Arab D Reservoir, Qatif Field(2011-08) Al-Nazghah, Mahmoud Hasan; Steel, R. J.; Kerans, C. (Charles), 1954-; Smith, Langhorne Bullitt, 1961-The Late Jurassic Arab D Formation in Saudi Arabia hosts the some of the world’s largest hydrocarbon reservoirs including Ghawar, the world’s largest oil field, and Khurais, the world’s largest supergiant to come into production in the last 5 years. Despite the vast oil reserves within the Arab D, and the central role of this reservoir at Ghawar in making up short-falls in global production, our understanding of the much fundamental characterization work both in terms of modern sequence stratigraphic reservoir frameworks and linked structural/fracture characterization. This study of Arab D reservoir at Qatif, immediately to the north of Ghawar, provides one of the first looks at a modern sequence analysis of this producing interval and illustrates that porosity zonations, and ultimately flow unit architecture may be substantially different than currently in use. The Arab D of the Arabian Plate is a carbonate ramp system of exceedingly low angle (<1o) developed during a low-eustatic-amplitude greenhouse Milankovitch setting. Combined macroscopic and petrographic data analysis allowed recognition of nine depositional facies: 1) spiculitic wackestone, 2) Planolites-burrowed wackestone, 3) bioturbated skeletal-peloidal packstone, 4) pelletal packstone, 5) peloidal-skeletal grain dominated packstone, 6) peloidal-skeletal grainstone, 7) skeletal-ooids grainstone, 8) cryptalgal laminites and 9) anhydrite. The depositional facies defined are used to interpret three facies tracts from deep to shallow across the ramp profile: 1) low energy sub-storm wave base (SWB) dominated facies that may illustrate disaerobic tendencies, 2) high energy within-fair-weather-wave-base ramp-crest or mid-ramp facies including foreshore and upper shoreface oolitic and skeletal grainstones that define one of the key reservoir pay zones and 3) back-barrier tidal flats consisting of cryptalgal laminites, sabkha-type anhydrites, and salina-type anhydrites. Three high frequency sequences are defined: QSEQ 1 is asymmetrical, dominated by subtidal lithofacies; and QSEQ 2 and QSEQ 3 are symmetrical and record a complex history of the fill on an intrashelf basin. Detailed cycle-scale correlations using core-based cycles and wireline log patterns allowed a cycle-scale correlation framework to be established that illustrates a north to south progradation of the Arab D reservoir strata, building landward from the Rimthan Arch. Diagenetic features observed in the Arab D reservoir include fitted fabric (chemical compaction), dolomitization, and cementation. These features play a major role altering reservoir quality properties as they essentially control fluid flow pathways which ultimately alter primary porosity and permeability.