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Results
Summary Systematic time-lapse pulsed neutron capture (PNC) logging was conducted during a two-year steam foam mechanistic field trial in a previously steamflooded reservoir. The producing reservoir tested was the Monarch Sandstone, which is composed of thinly inter-bedded sandstones, siltstones, and diatomaceous mudstones at the base, coarsening-upward to massive conglomerates and sandstones with a few interbedded mudstones at the top. Observation wells were drilled in the study area, one of which was continuously cored through the reservoir interval (578 feet). Two of these cased wells were emptied to facilitate better temperature logging. Uncalibrated PNC log responses in the air-filled wells were normalized (calibrated) to water-filled conditions with transform functions empirically determined in the same wells. The normalized logs were used to generate a series of steam/gas saturation profiles that indicate clearly the dynamics of the fluid and foam in the reservoir during the experiment. Enhanced precision and bed resolution of the PNC logs were necessary for interpretations in the thinly bedded part of the reservoir. The time-lapse profiles were capable of delineating flow units down to a few feet in thickness and showed excellent consistency with lithologic variations described in the core. In addition, the PNC log detected mudstone layers as thin as six inches. Correlations between neutron capture cross sections (sigma), mineralogy, and rock chemistry, all from analyses of core samples, were examined to investigate additional use of the PNC logs for steamflood reservoir characterization. As expected, sigma increased with increasing clay/mica content. However, a more significant correlation was noted between sigma and diatomite content, which is due to the boron in the diatomite. This finding may result in improved stratigraphic correlations of the more laterally continuous diatomaceous mudstones based on PNC logs, with significant impact on the characterization of reservoirs of this type. The PNC log data from the field trial, when used in conjunction with core, temperature, and pressure data, was critical in developing a better understanding of foam generation and propagation in the reservoir. Furthermore, it minimized the time and cost required to successfully complete the field trial. Introduction In the management of a steamflooded reservoir, it is important to both monitor and predict steam movement in order to optimize steam sweep efficiency and heating energy usage. To these ends, the pulsed neutron capture log (PNC) has been providing useful information in steamfloods in the San Joaquin Valley and elsewhere, along with other logging methods. In most steamflood operations, steam movement and distribution are primarily controlled by gravity and reservoir geology - vertically by barriers, and horizontally by sand geometry. The more complex the geology, the more difficult it is to predict steam movement Cores and openhole logs have been providing geologic information before and during a steamflood.
- North America > United States > California > San Joaquin Basin > Midway-Sunset Field > Webster Formation (0.99)
- North America > United States > California > San Joaquin Basin > Midway-Sunset Field > Monterey Formation (0.99)
- North America > United States > California > Monterey Formation (0.99)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Thermal methods (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
Summary Coreflood experiments in naturally heterogeneous sandstone outcrop cores were conducted and simulated. Displacements included waterfloods and polymerfloods using tracers for the oil and/or water during both single-phase flow and two-phase flow. Those involving the displacement of viscous polymer solution were unstable. The corn were characterized by polymer solution were unstable. The corn were characterized by air permeability measurements on each square centimeter of each face and by C.T. scans of cross-sections of the core spaced one Centimeter apart along the length of the core. Fine-grid simulations were then made using these characterization data as input. The agreement between the experiments and simulations is good. Simulations using coarser grid physical descriptions were then made using effective properties. Introduction The results given in this paper summarize our efforts to use numerical simulation to analyze our own experimental data on naturally heterogeneous sandstone cores called Antolini sandstone. Antolini sandstone is an eolian outcrop in northern Arizona. A series of displacements were conducted in two samples of this outcrop. Experiment Al is one of several corefloods done by Wreath to study polymerflooding in heterogeneous cores. Experiment Ahtolini-4 is one of several corefloods done by Ganapathy to study the effects of heterogeneity on both miscible and immiscible displacements. In both cases, the cores were characterized by a combination of air permeability measurements on each square centimeter of each face of rectangular slabs of sandstone, C.T. scans of cross-sections spaced one centimeter apart along the length of the cores ad by multiple water and oil tracers. Fine-grid simulations were then made using this characterization data ad comparisons made with the pressure, tracer and production data from these corefloods. The chemical flooding simulator developed at The University of Texas called UTCHEM was used for these simulations. An important factor that distinguishes this work from other results reported in the literature is the use of an outcrop sandstone rather than either artificially heterogeneous cores or small samples of reservoir cores. We present an integrated approach that includes experiments using an air minipermeameter, C.T. scanning, multiple tracer experiments in both water and oil, pressure data, oil recovery data and both stable and unstable polymer displacements in large samples of heterogeneous outcrop sandstone combined with both fine-mesh and coarse-mesh simulations. The use of this particular outcrop sandstone for these and other similar experiments has a number of advantages over the use of reservoir cores because we can readily obtain large samples and as may samples as needed with variable degrees of heterogeneity. It also has advantages over artificially heterogeneous permeable media because as a practical matter samples of consolidated sandstone with large and practical matter samples of consolidated sandstone with large and variable heterogeneity on a variety of scales are difficult and expensive to make and may still not minic nature in some ways we may desire. For example, in addition to the macroscopic flow characteristics that are included in this paper, results of how the residual oil saturation differs between waterflooding and polymerflooding can be found in Wreath.
Summary This paper presents a technique for monitoring CO2 flood response and performance using wireline-derived petrophysical data. Results obtained with this technique are useful for quantifying CO2 saturation, monitoring flood progress and vertical sweep, identifying potential out-of-zone injectant losses, and detection of non-responding layers. The basis for identification of CO2 is the gas effect on neutron log porosity. Using sonic porosity as an estimate of total porosity, gas (CO2) is identified in zones where corrected neutron porosity is less than total porosity. Neutron porosity is obtained in flowing producers using a pulsed neutron log (TDTP). The porosity correction is empirical and was derived using data from a recent CO2 pilot test. Gas saturation data derived with this method are in agreement with independent estimates available from a CO2 pilot project. Examples are given to show the application of the method in the Denver Unit. This method should be generally applicable to other ongoing Permian Basin CO2 floods. Introduction CO2 flooding is widely recognized as a viable technique for enhanced oil recovery (EOR). One element vital to the technical and economic success of any CO2 flood is the optimum utilization of CO2 injectant. Poor vertical sweep by CO2 or out-of-zone losses of CO2 may significantly impact forecast oil recovery and make continued CO2 injection economically unattractive. Therefore, real-time monitoring of areal and vertical flood progress should be considered a vital part of CO2 flood surveillance. Wireline log data can be used to monitor CO2 flood progress and vertical sweep. The presence of gas (hydrocarbon or CO2) causes a change in neutron log count-rate ratio and intrinsic neutron absorption cross section, which can be used to derive gas saturation. These effects can be used to (1) identify layers responding to CO2 injection and (2) quantify CO2 saturation. Wireline monitor programs generally use time-lapse logging with compensated neutron and/or pulsed neutron log suites, and are commonly carried out in pilot projects with wellbores exclusively dedicated for logging.
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- (34 more...)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
- Information Technology > Architecture > Real Time Systems (0.55)
- Information Technology > System Monitoring (0.34)
Summary Permeability heterogeneity in porous media is evaluated with standard-pressure and production-history measurements from miscible displacements. Variations in the production history with mobility ratio and deviations of the pressure history from an idealized response provide complementary information on permeability heterogeneity. These heterogeneity tests have been permeability heterogeneity. These heterogeneity tests have been developed to assist in core sample selection for unsteady-state relative permeability tests and other transient displacement tests. Introduction Many laboratory tests used to characterize the ability of porous materials to transmit fluids involve transient displacement. During any displacement test, at least one recognizable feature, such as saturation or phase composition, is propagated through the porous medium in the direction of flow. The unsteady-state porous medium in the direction of flow. The unsteady-state relative permeability test is an example of a displacement test in which the saturation and effective viscosities are transient properties. A variety of EOR methods commonly are investigated properties. A variety of EOR methods commonly are investigated in the laboratory by use of displacement tests with transientsaturations and phase compositions. Displacement tests usually rely on the assumption of uniform permeability for measurement interpretation. Unsteady-state relative permeability tests on heterogeneous samples have been shown to violate the assumptions required by explicit interpretation methods, which lead to errors in the relative permeability analysis. Heterogeneity will be classified as transverse or longitudinal to facilitate the discussions in this paper. Transverse heterogeneity refers to permeability variations overcross sections orthogonal to the flow direction. Longitudinal heterogeneity refers to permeability variations that are strictly a function of position permeability variations that are strictly a function of position along the flow axis. Although heterogeneous cores generally will not fit into either classification, the miscible-displacement tests to be discussed have features that differentiate these two heterogeneity modes. Permeability Heterogeneity Characterization Permeability Heterogeneity Characterization Permeability heterogeneity characterization is not routine because Permeability heterogeneity characterization is not routine because of limited available experimental methods and difficulties in interpreting heterogeneity results. The most frequently used heterogeneity test has been the unit-mobility-ratio miscible-displacement test. The mixing of miscible fluids in 1D flow through homogeneous porous media is known to follow the dispersion equation (1) The hydrodynamic dispersion coefficient, K, is used to model the bulkeffective mixing rate for miscible fluids flowing through porous media. porousmedia. Capacitance effects in the production history from this type of test can be used to detect heterogeneity. Capacitance production behavior refers to along period of low-level production of the displaced phase after an early breakthrough of the injected phase. The 1D dispersion model (Eq. 1) cannot match production histories with capacitance effects, which generally have been modeled by including mass transfer between a flowing and nonflowing fraction of pore space. Although the unit-mobility-ratio miscible displacement determines heterogeneity when capacitance occurs, permeability heterogeneity does not always produce capacitance permeability heterogeneity does not always produce capacitance effects. Transverse heterogeneity may enhance longitudinal dispersion without demonstrating capacitance effects or any other deviations of the production history from a dispersion model. Longitudinal permeability heterogeneity will not produce a characteristic response from a unit-mobility-ratio miscible displacement because the production history is sensitive only to variations in porosity and dispersivity. Therefore, it is not always possible to identify permeability heterogeneity from a unit-mobility-ratio miscible-displacement test. The use of favorable-mobility-ratio miscible displacements provides a comparison test to the unit-mobility miscible provides a comparison test to the unit-mobility miscible displacement to aid in the diagnosis of heterogeneity. Mobility ratio values less than 1 are favorable because of good displacement efficiency. Giordano et al. studied favorable-mobility-ratio miscible displacements in aheterogeneous porous medium by use of numerical simulation of miscible displacement in a square, 2D random permeability field. Results from these calculations show sharpening of the breakthrough curve at the lower mobility ratios compared with the unit-mobility-ratio test. For the particular heterogeneity field used in these simulations, no differences were detected between the 0.1 mobility-ratio displacement and the 0.01 mobility-ratio displacement. The permeability field contains random permeability values drawn from a normal distribution where the permeability values drawn from a normal distribution where the ratio of the standard deviation to the mean is 0.5. The permeability is uniform over squares with sides of length 0.1 permeability is uniform over squares with sides of length 0.1 times the total length of the porous medium. Experiments that Sorbie et al. performed on a Clashach quarrysandstone give further evidence of reduced dispersion at lower mobility ratios. A favorable-mobility-ratio miscible slug test (M = 0.33) resulted in a dispersivity (for the leading edge) close to one-half the dispersivity found for a unit-mobility-ratio test. However, further decreases in the mobility ratio (M = 0.125) did not influence dispersivity. These results indicate that stable, miscible flow is sensitive to a certain range of the mobility ratio. Comparing a miscible displacement at unit mobility ratio with a miscible displacement at one or more lower mobility ratios provides a means to determine whether permeability heterogeneity enhances dispersion. The average effective dispersion for equal mobility fluids in a heterogeneous porous medium is a result of pore-level mechanisms (which create dispersion in a homogeneous porous medium) plus macroscopic deviations from 1D flow caused by permeability heterogeneity. A favorable mobility ratio can suppress deviations from 1D flow, thereby reducing effective dispersion. The sensitivity of the dispersivity to the mobility ratio has theoretical implications with regard to modeling favorable-mobility-ratio miscible displacement. The mobility ratio as used in this paper is strictly the endpoint mobility ratio. The sensitivity of the dispersion coefficient to the endpoint mobility ratio might suggest that the dispersion coefficient should be a function of the local mobility ratio (i.e., a function of the concentration). However, experimental results here and elsewhere indicate that the linear dispersion model (Eq. 1) is sufficient to match the production behavior. SPEFE P. 112
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
Summary From phase and wettability studies on bulk phases, we predicted the fluid-fluid-fluid dispersion morphologies that could predicted the fluid-fluid-fluid dispersion morphologies that could be expected for ex-situ dispersions (formed before injection) and for the dispersions after they were injected into a porous medium. From videomicroscopic studies of the flow of the dispersions through an etched microvisual cell, we determined the actual morphologies of the dispersions during flow. Three different wettability conditions and three different morphologies of flowing dispersions were observed. Introduction Where two fluids, Fluids A and B (e.g., water and oil, or gas and oil), make contact with a reservoir mineral, Mineral D (e.g., quartz), the geometry of this contact is described by the apparent contact angles, and (Fig. 1a). This set of angles, together with the various effects they cause, are called the wettability. It is well-known that such fluid-fluid-solid wettabilities play central roles in imbibition, relative permeabilities, and oil recoveries. permeabilities, and oil recoveries. Although it makes the flow conditions much more complicated, often @ fluid phases, Phases A through C (e.g., water, gas, and oil), along with Mineral D, are encountered in oil production. In such a situation (Fig. lb), the geometry of the contact line among the three fluids likewise is described by three apparent contact angles, similar to the, and for the fluid-fluid-solid case. Recently, it has been shown that fluid-fluid-fluid wettabilities also play key roles in oil recoveries: oil recoveries are substantially greater when the oil-rich phase completely wets, or spreads, across the interface between the two other fluids. Two well-known problems of gasflooding are viscous fingering and gravity override. Currently, foams, emulsions, and other kinds of fluid dispersions are being developed to improve mobility control in CO2 flooding and other kinds of EOR. (Throughout this paper, "dispersion" refers to droplets or bubbles of one or more paper, "dispersion" refers to droplets or bubbles of one or more fluids in another fluid phase.) In such cases, the tendency of the oil-rich phase to spread between the "gas" and "water" may have an important beneficial effect on the ability of the "foam" to reduce mobility in large portions of a reservoir. The exact role of the fluid wettabilities in foam stabilities is unclear, but it is thought that the ability of the oil to spread may have a serious effect on the stability of foam in the presence of oil. As long as only two fluid phases, Phases A and B, are present, only two nonmultiple dispersion morphologies are possible: A-in-B (often written as A/B) and B-in-A (B/A). However, when three fluid phases (Phases A through C) are present, the number of theoretically possible dispersion present, the number of theoretically possible dispersion morphologies greatly increases. For example, if Phase A is the continuous phase, the morphology might be either C-in-B-in-A (Fig. 2a) or B-and-C-in-A (Fig. 2b), whereas if Phase C is the continuous phase, the morphology might be either A-in-B-in-C (Fig. 2c), or phase, the morphology might be either A-in-B-in-C (Fig. 2c), or A-and-B-in-C (Fig. 2d). Moreover, regardless of which phase is the inner-most phase (Fig. 2a or Fig. 2c), it may be dispersed as multiple droplets; Fig. 2e illustrates multiple droplets of C for the C-in-B-in-A morphology. It is well-known that the flow properties of A/B and B/A dispersions greatly differ from one another. Hence, it is to @ expected that the flow behavior and oil recoveries associated with three-fluid dispersions likewise will be different for different dispersion morphologies. The wettability conditions of the three fluids and of the solid phase are thought to play central roles in determining the morphologies Of three-Phase dispersions. As Fig. 1b illustrates, for four phases (Phases A through D), there are four different hypothetically possible three-Phase contact lines that must be considered: A, B, C; A, B, D; A, C, D; and B, C, D. Figs. 3 and 4 illustrate different bulk-phase wettability combinations. For example, if Fluid B wets the interface between Fluids A and C, as illustrated in Fig. 3 for bulk phases, the expected dispersion morphologies are A-in-B-in-C or C-in-B-in-A. The wettability of Solid D may determine whether Fluid A or C is continuous. For example, in Fig. 3a, Fluid A wets the interface between Fluid B and Solid D, which suggests the C-in-B-in-A dispersion morphology (Fig. 2a). However, in Fig. 3b, Fluid C wets the interface between Fluid B and Solid D, implying the A-in-B-in-C dispersion morphology (Fig. 2c). If the contact angles among Fluids A through C are all nonzero (Fig. 4), then the expected morphologies are A-and-B-in-C and Band-C-in-A. In Fig. 4a, Fluid A wets the interfaces between Fluid B and Solid D and between Fluid C and Solid D, respectively. Therefore, one might expect the dispersion morphology B-and-C-in-A (Fig. 2b). In Fig. 4b, Fluid C wets the interfaces between Fluid A and Solid D and between Fluid B and Solid D, respectively; hence, one might expect the dispersion morphology A-and-B-in-C (Fig. 2d). The spreading coefficient, SIK, determines whether one fluid wets and spreads across the interface between two other phases so that the latter two phases are not in physical contact. The change between the spreading and nonspreading conditions is called a "wetting transition. For bulk phases (Figs. 3 and 4), (1) where, and are the interfacial tensions (IFT's) between phase pairs I and J, I and K, and J and K, respectively. (Here, I through K are three of the Phases A through D.) When SIK > 0, Fluid J spreads across the interface between Phases I and K; when SIK < 0, Fluid I spreads across the interface between Phases J and K. However, predictions of dispersion morphologies from bulk-phase wettability measurements may, in some cases, be misleading because the spreading coefficient depends on the size of the droplets. For droplets of radii rj and rK, the spreading coefficient as a function of the droplet sizes is (2) Furthermore, the IFT's and, thus, the contact angles among three phases, are not constant; instead, they depend on the temperature, pressure, and phase compositions. Hence, a wetting transition may occur among spreading by Phase I, spreading by Phase I, and no spreading by any phase, if a change of one thermodynamic variable and/or of droplet radii makes an appropriate change in the spreading coefficient. Droplet radii depend on the flow rate, the pore-throat geometries, and fluid properties. pore-throat geometries, and fluid properties. Thus, the morphologies and flow properties of three-fluid dispersions may depend interactively on both the thermodynamic and fluid dynamic conditions through the surface tensions and droplet radii. Wetting transitions have been known for gas-liquid-solid and liquid-liquid-solid phase triads.
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Multiphase flow (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)
Summary. This paper summarizes a study performed to evaluate nitrogeninjection in Ekofisk and includes a geological description, measurement ofphysical properties, model development, mechanistic studies, and physicalproperties, model development, mechanistic studies, and cross-sectionalnitrogen-injection simulations. Introduction Ekofisk field is an overpressured, naturally fractured, chalk reservoir inthe Norwegian sector of the North Sea in about 235 ft of water. Ekofisk iscomposed of 700 to 1,000 ft of productive chalks with 350 to 500 ft in the Ekofisk formation (Danian) and 350 to 500 ft in the Tor formation(Maastrichtian). These formations are separated by a 50- to 90-ft-thick tightzone. The initial reservoir pressure was 7,120 psig at 10,400 ft subsea. The bubblepoint pressure is about 5,545 psig at the reservoir temperature of 268 degrees F. Initial hydrocarbons in place include 6.7 ร 109 bbl oil and 10.3 Tscf gas. The field is a north/south-trending, elongated anticline (Fig. 1). Production from Ekofisk began in 1971. The projected primary recovery, withhydrocarbon gas injection in the Ekofisk projected primary recovery, withhydrocarbon gas injection in the Ekofisk formation in excess of sales, isforecast to be 24 % of the equivalent original oil in place, assuming 1 bbl oilequals 6 Mscf. Enhanced recovery by water injection in the lower Ekofisk and Tor formations is projected to yield 350 ร 106 bbl oil equivalent. Nitrogen injection in the upper Ekofisk formation at 200 MMscf/D is beingevaluated as a way to accelerate gas sales and to increase recovery. The proposed nitrogen-injection wells are located in the crest of the field, asshown in Fig. 1. Calculation of displacement in the upper Ekofisk is complicated by thehighly fractured nature of the chalk. This paper describes the work performed to evaluate nitrogen injection in Ekofisk and includes geological performed toevaluate nitrogen injection in Ekofisk and includes geological descriptionwork, measurement of physical properties, model development, mechanisticstudies, and cross-sectional nitrogen-injection simulations. The geological description includes a statistical analysis of the Ekofisk fractures, description of sedimentology, and the identification and description of barriers to vertical flow. Physical properties measured and processed for thisstudy include nitrogen/crude-oil swelling and processed for this study includenitrogen/crude-oil swelling and vaporization PVT, gas/oil capillary pressure, interfacial tension (IFT) as a function of pressure and composition, andnitrogen/gas and nitrogen/oil diffusion data. Model development includes an extended beta PVT model, which is a function of pressure and nitrogen composition; mass transfer by diffusion; gas/oilcapillary pressure as a function of pressure and nitrogen concentration; andthe incorporation of rock compressibility as a function of net overburdenpressure. Mechanistic studies illustrate the concept of matrix/matrix continuity andthe effects of diffusion, gravity, viscous forces, and capillary pressure onoil and gas recovery. Detailed cross-sectional models were developed with the fracture analysisfrom Wells K-04 and A-06. These models were used to evaluate the effects ofvertical and areal permeability distribution, gas/oil capillary pressure, diffusion, and kv/kH on displacement of oil and gas by nitrogen at 4,000 psia. The results indicate that Wells K-04 and A-06 behave similarly, even thoughindividual layers in these wells behave differently. Fine-grid simulations ofthese wells were matched with a coarse-grid 2D model with two sublayers, corresponding to each field model layer, or with channeling logic (amathematical approximation to account for injected-gas channeling resulting from fine-scale heterogeneities) and the same number of layers as in thefull-field 3D model. Geological Description An extensive geological study on the Ekofisk formation was conducted as partof this project. The geological study consisted of five related investigations:detailed fracture descriptions, sedimentological study of slabbed cores, correlation of the fracture description to the sedimentological and/or well-logdescription on a well-to-well and/or layer-to-layer basis, and determinationand correlation of barriers to vertical flow. The productive -interval of the Ekofisk formation is divided in to threeupper geological layers (EA, EB, and EC) and one lower layer (ED). Five layersare used in the Ekofisk full-field model, with the geological Layer EArepresented by Layers 1 and 2. The fracture analysis represents 1.122 ft of core from 11 wells in the upper Ekofisk formation. The foot-by-foot analysis describes the number and type offractures, the fracture orientation, where possible, and whether the fractureis open or partially or completely mineralized. Fracturing in the Ekofisk isprimarily tectonic, while fractures in the Tor are predominantly associatedwith stylolites. The tectonic fractures in the Ekofisk are steeply dipping, with an average dip of 75 degrees, and have associated conjugate fractures thatdip at an average of 65 degrees. The resulting matrix blocks are elongatedprisms with cross-sectional dimensions of 0.3 to 3 ft and lengths of 3 to 12ft. A foot-by-foot sedimentological study was performed on stabbed cores fromseven wells. The chalk was categorized into eight sedimentological facies:three deposited in place (laminated pelagic, argillaceous, and burrowedmottled) and five redeposited through gravity flow mechanisms (slide/slump, pebble floatstone, homogeneous mudflow, thin burrowed mudflow, and skeletalgrainstone). Correlation of the fracture and sedimentological descriptions toconventional well logs was attempted with statistical techniques called"clustering". The model obtained by clustering did not have asufficient degree of confidence to be used to predict fractures orsedimentology in the uncored intervals. A layer-by-layer statistical analysis of the fracture and sedimentologicaldescriptions was made for each well. The information analyzed includedfrequency of fracture counts per foot for a given sedimentological type, continuous feet of each sedimentological type, and fractured/nonfractured core, and total feet of each sedimentological type and of a given fracture intensity. This information was entered into a data base for display in a well-log format, with 11 items shown in various channels. Interpretation of Geological Study Results. The most important aspect of thegeological study is that the Ekofisk formation is highly heterogeneous. This isbest shown by inspection of the individual presentations of the fracture logsand comparisons of the statistical results on well-to-well and layer-to-layerbases. The frequency plots for both fracture intensity and sedimentology showvery similar shapes. Fig. 2 shows the frequency of continuous intervals of openand closed fractures vs. thickness for one layer in one well. Most of theintervals of a given type are in the 1-to-10-ft range. Sometimes, however, nearly one-half the total thickness of a geological layer is represented byindividual layers >10 ft. The unfractured intervals show similardistributions to the fractured intervals. Thus, the upper Ekofisk formation isa series of alternating fractured and unfractured layers, with most layers lessthan 10 ft thick. Within a given layer, there is little well-to-wellcorrelation of any intensely fractured or nonfractured layer. A significantnonfractured interval may appear only at the top of a geological layer in onewell and only at the bottom of the same geological layer in an adjacentwell. Vertical Permeability. An important part of the geological description isthe determination of the frequency of barriers to vertical flow. SPEFE P. 151
- Europe > Norway > Norwegian Sea (0.85)
- Europe > Norway > North Sea > Central North Sea (0.34)
- Geology > Sedimentary Geology (1.00)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.68)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock (0.34)
- South America > Colombia > U Formation (0.99)
- Europe > United Kingdom > North Sea > Central North Sea > Utsira High > PL 006 > Ekofisk Formation (0.99)
- Europe > Norway > North Sea > Central North Sea > Central Graben > PL 018 > Block 2/4 > Greater Ekofisk Field > Ekofisk Field > Tor Formation (0.99)
- (2 more...)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Naturally-fractured reservoirs (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Faults and fracture characterization (1.00)
- (7 more...)
Determining the Productivity of a Barrier Island Sandstone Deposit From Integrated Facies Analysis
Sharma, Bijon (Natl. Inst. for Petroleum and Energy Research) | Honarpour, M.M. (Natl. Inst. for Petroleum and Energy Research) | Jackson, S.R. (Natl. Inst. for Petroleum and Energy Research) | Schatzinger, R.A. (Natl. Inst. for Petroleum and Energy Research) | Tomutsa, Llvlu (Natl. Inst. for Petroleum and Energy Research)
Summary Two crossplot techniques, based on core-calibrated resistivity, porosity, and gamma ray (GR) logs, are described that distinguish barrier porosity, and gamma ray (GR) logs, are described that distinguish barrier island sandstones from genetically different nonbarrier sandstones in the Muddy sandstone reservoir in Unit A of Bell Creek field, Montana. The barrier island sandstones are separated further and grouped into two log facies, one consisting of highly productive facies (foreshore, shoreface, etc.) and the other, a less-productive facies (lower shoreface). The distinct crossplot patter for each facies group is due to similar petrophysical properties of each facies group resulting from deposition petrophysical properties of each facies group resulting from deposition within a unique depositional setting. Fluid production results from primary, secondary, and two EOR pilot projects indicate that in the barrier island reservoir at Bell Creek, projects indicate that in the barrier island reservoir at Bell Creek, the distribution of facies, with their characteristic reservoir properties and heterogeneities, dominates primary production, waterflood-sweep efficiency, distribution of residual oil saturation, and the performance of the chemical EOR pilot projects. Introduction The generally prolific production from oil and gas fields in barrier island clastic deposits results from the excellent porosity and permeability of sandstones deposited in relatively shallow, agitated permeability of sandstones deposited in relatively shallow, agitated marine waters. Sediments flanking main barrier sandstone deposits are organic-rich, lagoonal and deepwater, fine-grained deposits that often serve as excellent source beds for petroleum. Process-oriented sedimentological studies have provided better understanding of sedimentary structures, sequence of facies, and other features in different subenvironments that contribute to building barrier island sandstone deposits. Because each barrier island facies (beach, shoreface, dune, etc.) was deposited within a unique setting of wave energy, tidal range, and water depth, the sandstones from each subenvironment tend to have similar petrophysical properties (porosity, permeability, grain-size petrophysical properties (porosity, permeability, grain-size distribution, etc.) at the time of deposition. Davies et al. first demonstrated the remarkable similarity of internal structure and texture in different facies of the modern barrier island in Galveston, TX, with two ancient barrier complexes: one in the Lower Cretaceous of Montana and the other in the Lower Jurassic of England. A subsequent study revealed that major barrier island sandstone facies have recognizable characteristics and may also have some significant variations, depending on local wave conditions and tidal range. Recognizable characteristics of different facies of barrier island sand-stones have been investigated with thin-section analysis. Because of the relative uniformity of depositional processes in each facies, the predictability of fluid production from barrier island reservoirs can be greatly augmented from an understanding of the spatial distribution of thicknesses, flow properties, and geological heterogeneities in each facies. Subsequent to sandstone deposition, such secondary processes as diagenesis or tectonic events may severely affect the distribution of flow properties in different facies. Understanding depositional characteristics, however, leads to understanding the effect of secondary diagenetic processes. In this paper, we describe two crossplot techniques, based on interpretation of log and core data, that can effectively distinguish some of the barrier and associated nonbarrier island sandstone facies. We use these techniques to group facies with similar petrophysical properties, and then we study the different facies petrophysical properties, and then we study the different facies groups for distribution of reservoir properties and geological heterogeneities and variations in thickness and structure. The usefulness of facies interpretation for predicting productivity of sandstones in the different facies is demonstrated by a productivity of sandstones in the different facies is demonstrated by a qualitative comparison of initial primary and EOR production from Bell Creek field with the areal distribution of reservoir properties and sandstone geometry in the different facies groups. A primary objective of this investigation was to demonstrate that fluid injection and production predictions would be greatly improved if barrier island sandstone were divided into a number of facies or groups of facies with each group of similar facies characterized separately, instead of the average petrophysical properties of an entire sand-stone thickness being studied.
- North America > United States > Montana (1.00)
- North America > United States > Texas > Galveston County > Galveston (0.24)
- North America > United States > Wyoming > Wind River Basin > NPR-3 > Muddy Formation (0.99)
- North America > United States > Wyoming > Powder River Basin (0.99)
- North America > United States > Montana > Powder River Basin (0.99)
- North America > United States > Montana > Bell Creek Field (0.99)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
Summary Fluid saturation development in long-core flood experiments is investigated. Information on ID fluid saturation distributions is obtained by labeling the fluid phases with nuclear tracers and detecting radiation with a movable detector. Various flood experiments were done on 2.5-ft [76-cm] -long sandstone cores. In miscible displacements where radioactive brine is displacing inactive brine, dispersion and ion adsorption are evaluated. Imaging saturation profiles during drainages and waterfloods gives information on saturation front velocity and time development of local saturation variations. Experimental results are compared with numerical results from a 1 D front-tracking black-oil simulator that incorporated homogeneities and capillary effects. Surfactant floods were investigated to test the applicability for EOR studies further. Introduction Imaging multiphase flow in long cores of reservoir rock can improve our understanding of the displacement mechanisms of oil recovery processes. Because recordings of produced fluids yield only the average saturation of an entire core, recording the fluid saturations as functions of time and position will provide more in-formation about the flow processes. Inclusion of reservoir temperature and pressure is essential to any laboratory study of oil production to ensure relevant flow and wetting properties. I Most imaging techniques currently used in laboratory research of petroleum recovery are not capable of working at these conditions. Imaging techniques with high-energy signals capable of penetrating pressure containments, however, have been reported. Initiated by experiences from these nuclear-imaging techniques, a long-core flow rig, designed to operate at reservoir pressure and temperature. was constructed and used to study multiphase flow in porous rocks. The dynamics of fluid saturation distributions in displacements is recorded by use of nuclear tracers that label fluid phases and a movable detector outside the pressure vessel that detects emitted gamma radiation. It has been argued in the literature that experimental results on flow behavior from flood experiments in short plugs of reservoir material are questionable because of severe end effects resulting from the sudden discontinuity of the capillary forces at the core ends. The significance of this disturbance on the flow pattern is a function of the core length, the flow velocity, the interfacial tension between the fluids, and the fluid characteristics. In these reported experiments, therefore. we use long cores from an outcrop with geologically relevant rock characteristics. Flow Rig Fig. 1 is a schematic of the flow rig. The main component of the rig is a 6.6-ft [2-m] -long cylindrical steel pressure vessel with a 2.8-in. [7-cm] ID and a 0.4-in. [1-cm] wall thickness. Cores up to 5 ft [1.5 m] long are coated with epoxy and embedded in a transformer oil inside the vessel. After the transformer oil is heated and pressurized. the rig can simulate the temperature and pressure conditions in a reservoir down to a 13,000-ft [4-km] depth, corresponding to a geostatic pressure of 15,000 psi [100 MPa] and a temperature of 250F [120C]. The core is equipped with end pieces designed to give an even fluid distribution over the end surface. Pumping the fluids against a backpressure regulator gives pore pressures of 10,000 psi [70 MPa]. Experimental flow rates may range from 0.01 to 10 mL/min. Injected fluids are labeled with radioactive tracers and subsequent gamma radiation is detected with a movable liquid N2-cooled, high-purity germanium detector (HPGe) outside the pressure vessel. The detector system is mounted on a trolley that is moved by a step motor. An optical encoder system reads the position of the detector with an accuracy of 0.002 in. [0.05 mm], independent of stalling or slipping of the step motor. The detector has a 2-key energy resolution at full width at half maximum (FWHM). It is placed inside a 4-in. [10-cm] -deep lead housing, which serves as a collimator, with a 0.2-in. [4-mm] -wide slit through which radiation from the core is accepted. The distance from the collimator to the center of the core is 2 in. [5 cm]. This collimator setup gives a spatial resolution for core imaging of 0.24 in. [6 mm]; i.e., radiation is accepted from an effective 0.24-in. [6-mm] wide slice of the core. The width of the collimator slit to be used must be evaluated with respect to the radioactivity in the slice to be measured. This activity depends on the radioactive concentration in the labeled phase, the phase saturation, and the porosity. Also important is the choice of detector-counting time, which usually is a compromise obtained when accounting for the width of the collimator slit, the desired accuracy in the saturation measurements, and the displacement-front velocity. The flow rig is equipped with computerized automation that includes data acquisition and process control. In regard to radiation and health hazards, the remote operation ensures safe conditions for operating personnel. Usually, a total amount of radioactive material of 1 mCi [3.7 ร 10โ7 Bq] dissolved in 1 L of brine is used during a displacement experiment. This amount exposes laboratory personnel to radioactive doses well below the international regulation for the whole-body, dose-equivalent limit of 50 mSv/a set by the Intl. Committee on Radiation Protection (ICRP). Although the operating distance can be longer, the rig is usually operated from a distance of about 15 ft [5 m]. At this distance, a person who works 8 hours a day will be exposed to less than 1 mSv/a or 2% of the maximum limit set by the ICRP for professionals who work with radioactive materials. Physical distance is the best protection against radiation in the laboratory because the intensity decreases as the square of the distance. After use, the radioactive liquid wastes are shipped in specially designed containers to the Inst. for Energy Technology in Kjeller, Norway. The institute is officially responsible for the storage and disposal of radioactive wastes in Norway.
- Europe > Norway (0.68)
- North America > United States (0.46)
Summary. In laboratory corefloods, polymer solutions used in EOR, such as partially hydrolyzed polyacrylamides (PHPA), often break through at less than 1 PV injected compared to the breakthrough of pure water. The rapid break-through is erroneously used to determine the ratio of pores accessible to polymer to total PV (accessible PV). Through numerical simulation and steady-state analysis, we show that the rapid break-through of such polymer solutions is not a measure of accessible PV. The only thing that can be inferred from the polymer solution breakthrough time is that polymer solution travels faster than water. Breakthrough time depends on the injected polymer concentration and shear rate. Our results significantly affect interpretation of polymer flow in porous media. Laboratory-measured polymer bulk properties are not those porous media. Laboratory-measured polymer bulk properties are not those that should be used in conventional reservoir simulation and pressure-transient test analysis of polymer solutions. The show two pressure-transient test analysis of polymer solutions. The show two different forms of the same partial differential equation used to describe rapid polymer breakthrough. The finite-difference solutions lead to two different polymer concentrations for each gridblock-a flowing concentration and a bulk (volume-average) concentration. The polymer-concentration-dependent properties required for each formulation polymer-concentration-dependent properties required for each formulation must be interpreted correctly. Rapid Polymer Breakthrough Interpretation Numerous laboratory experiments have demonstrated that water-soluble polymer travels faster in reservoir core than the average water-phase velocity. Thus, while an injected sodium pulse will break through at 1 PV of injected fluid, polymer breaks through faster, as illustrated in Fig. 1. Dawson and Lantz attributed this phenomenon to the existence of some pores that are not accessible phenomenon to the existence of some pores that are not accessible to the polymer. Liauh et al. also studied the phenomenon in detail. It is often assumed that polymer breakthrough time can be used to determine the ratio of pores accessed by polymer to total PV. This ratio is often called "accessible PV," but that is a misconception. This paper dispels that misconception. As Dawson and Lantz pointed out, rapid polymer breakthrough can be possible only if average polymer velocity is greater than average water velocity. Adsorption and dispersion affect the average polymer velocity, but we do not include their effects in the following discussion. Average water velocity is given as .........................................(1) Let tBTD be the dimensionless polymer breakthrough time (or the injected PV at polymer breakthrough). Because the polymer breaks through in tBTD PV's, it must travel at a velocity of ...........................................(2) which yields .........................................(3) Because tBTD as measured in the laboratory is less than 1.0, Up must be greater than Uw. The water in the pores has a wide velocity distribution because of variations in pore size and geometry; therefore, one possible explanation for the high average polymer velocity, Up, is that polymer is accessible only to larger (high-velocity) pores. Another explanation for rapid polymer breakthrough is the pores. Another explanation for rapid polymer breakthrough is the slip phenomenon, in which the polymer travels at the center of the pores where the velocity is higher than average. Both phenomena can be conceptually described by a two-layer porous-media model. One layer represents the high-permeability (high porous-media model. One layer represents the high-permeability (high velocity) pores accessible to polymer and water; the other layer represents the low-permeability (low-velocity) pores accessible only to water (Fig. 2). This does not consider the exclusion of available pores to flow as a result of polymer blockage. For blockage, polymer and tracer would break through at the same time because both follow the same flow channel. This contradicts Fig. 1. Because the polymer layer will have a higher velocity than the average water velocity, polymer will break through early. Polymer breakthrough time will depend on the velocity in the high-permeability layer. For single-phase flow, the polymer layer (Layer 1) velocity in terms of Darcy's law is ............................(4) where .......................................(5) The velocity for the second layer is ...................(6) and average water velocity is ..............................(7) Because P/L is the same for both layers, .........................(8) p. 359
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
Summary This paper discusses the importance of geological parameters of reservoir sandstones and their fieldwide distribution for proper planning and operation of EOR projects. Such parameters are gross and net pay thickness, permeability, porosity, grain size distribution, composition of detrital minerals, amount and type of mineral cements, and amount and type of clay minerals. Fieldwide distribution of these parameters is shown for the case history of the Hankensbuttel-Sud oil field in the Federal Republic of Germany. Overlaying the distribution maps made it possible to distinguish areas with excellent to good potential for chemical flooding from areas of fair to poor potential. On the basis of these results, a surfactant/ poly-mer flood pilot has been initiated in this field. poly-mer flood pilot has been initiated in this field. Geological Factors Influencing EOR Processes Sandstone reservoir quality and its suitability for EOR processes are determined by the following geological processes are determined by the following geological parameters:depositional features, tectonic parameters:depositional features, tectonic framework, and diagenetic alteration processes (Table 1). Depositional features-normally specific rock type and environment of deposition-include lateral and vertical continuity of reservoirs, primary reservoir anisotropies. sedimentary trap mechanisms, textural properties, detrital mineral composition, and primary matrix content. The lateral and vertical continuity of sandstones defines the areal extent and the thickness of a reservoir within a given trap. Sedimentary traps are those that form by depositional processes. Textural properties include grain size, sorting, processes. Textural properties include grain size, sorting, packing, shape, and rounding. Size and sorting have a packing, shape, and rounding. Size and sorting have a major effect on reservoir quality. The detrital mineral composition, as well as the primary matrix content, affects EOR processes. The tectonic framework is also essential for evaluating feasibility of EOR projects. It comprises the various tectonic trap mechanisms caused by folding, faulting, and fracturing of reservoir rocks, as well as fault configuration and type. Fracturing of brittle grains is associated primarily with faulting and/or intense folding. It may have primarily with faulting and/or intense folding. It may have an impact on the porosity of a reservoir. Diagenetic alteration processes commonly accentuate effects initiated by the original environment of deposition. Major processes are mechanical compaction (e.g., brittle vs. ductile grain deformation), chemical processes, such as mineral cementation (e.g., rim cements vs. occluding cements), and dissolution of chemically unstable components (e.g., carbonate) or dissolution and precipitation under changing temperature and pressure precipitation under changing temperature and pressure conditions. These processes are influenced mainly by pore water chemistry. Of all these processes, mineral cementations by quartz. carbonates, sulfates, sulfides, and hydroxides, as well as by clay minerals, influence EOR processes most strongly. Clay minerals-such as smectites, mixed-layer minerals, illite, kaolinite, and chlorite (Fig. 1)-play an especially important role as rather reactive cementing minerals in sandstones. Solitary clay particles vary in size and are normally of a platy, flaky, and/or fibrous shape. They occur as pore linings or as loose pore-filling aggregates. Clay minerals can greatly reduce permeability by effectively blocking pore throats, even as very thin pore linings; increase sensitivity to low-salinity fluids because of their small particle size, large surface area, and specific ion exchange capacity; and increase irreducible water saturations. Such interactions may lead to a general degradation in reservoir quality and therefore are significant for EOR operations. Case History The application of geological observations and measurements to a specific EOR project is demonstrated by the example of the Middle Jurassic Hankensbuttel-Sud oil field, one of the major producing fields in the Federal Republic of Germany (Fig. 2). This oil field, a truncation trap, is situated at the northwestern rim of the Mesozoic Gifhorn Trough. Oil production is from the Dogger Beta Sandstone, which was deposited in a shallow marine environment. Silty to very fine sheet sands predominate, and fine to medium shoestring sands occur to a minor extent. The sandstone is divided into two horizons separated by a claystone sequence (33 m [108 ft] thick). The Upper Sand contains 92% of the field's original oil in place (OOIP) and contributes 81 % of the present total production. p. 89
- Europe > Germany > Lower Saxony (0.49)
- North America > United States > Oklahoma > Creek County (0.44)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (1.00)
- Geology > Mineral > Silicate > Phyllosilicate (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)