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Results for “Journal of Petroleum Science and Engineering”

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11 recordsLinked to original sources
USGS2019

A fuzzy logic approach for estimating recovery factors of miscible CO2-EOR projects in the United States

"Recovery factor (RF) is one of the most fundamental parameters that define engineering and economical success of any operational phase in oil and gas production. The effectiveness of the operation, e.g. CO2-EOR (enhanced oil recovery with carbon dioxide injection), is usually defined by multiplying the resultant recovery factor by the original oil in place. Moreover, investment decisions for such engineering projects are also performed based on predicted recovery factors. Despite its importance, though, it is not easy to predict recovery factors as they are affected by many factors including the type of the recovery process, reservoir type, fluid properties, reservoir heterogeneity, depth, thickness, to name a few. The usual method of estimating recovery factors is laboratory experiments or numerical modeling, each of which has their own limitations due to data requirements, boundary conditions and scale effects. In this work, a fuzzy inference system approach has been adopted to predict miscible CO2-EOR recovery factors of the major field applications in the United States with the premise that it can be used as a guidance tool for making decisions based on different inputs. The fuzzy system was build using a Mamdani-type fuzzy logic inference engine, and by using reservoir data compiled from different sources as inputs and recovery factors gathered from a literature survey. Due to the limited number of field cases that could be used for this purpose, 24 sets of applications were included in the study. Selected input variables were water saturation after waterflood (Sorw), well spacing, porosity, permeability, depth, net pay thickness, initial pressure, API gravity of oil, hydrocarbon pore volume CO2 injected, and reservoir lithology. The type of membership functions were decided based on the system’s predictive performance. The model showed reasonable predictive capability for the field observations of recovery factor despite the complexity of this parameter. In addition, since the fuzzy solution was multi-dimensional due to multiple inputs, system behavior was used to demonstrate response of miscible CO2-EOR recovery factor to different inputs. "

Journal of Petroleum Science and Engineering↗
USGS2020

Well predictive performance of play-wide and Subarea Random Forest models for Bakken productivity

In recent years, geologists and petroleum engineers have struggled to clearly identify the mechanisms that drive productivity in horizontal, hydraulically-fractured oil wells producing from the middle member of the Bakken formation. This paper fills a gap in the literature by showing how this play’s heterogeneity affects factors that drive well productivity. It is important because understanding the relative strength of productivity drivers and how predictors vary spatially facilitates best-practices for well site selection and well completion design. The paper describes an application of the Random Forest (RF) machine learning technique to identify these mechanisms and to evaluate their importance across 9 subareas of the North Dakota portion of the Bakken play. The study examined productivity of 7311 wells initiating production from 2010 through 2017. Well productivity varied considerably across the 9 subareas within the play, so it was not surprising that the dominant predictors, the initial 180-day water cut and the 30-day initial gas production, vary spatially to mirror local conditions that strongly affect well productivity. The relative importance of well completion predictor variables, that is, the numbers of fractures stages per well, volume of injected proppant per stage, volume of injected fluids per stage, and lateral length, varied considerably across the subareas. Statistical permutation tests are presented that generally confirm the importance rankings. Subarea Random Forest models explained from 50 percent to 82 percent of the variation in productivity test samples while the play-wide model explained 73 percent of the test sample well productivity. Weakness in the predictive ability of the Random Forest models are traced to the limited variability in the training data. Implications of the empirical findings regarding the Bakken play for operators and for research and government institutions are discussed in the concluding section.

Montana, North Dakota, South Dakota↗
USGS1987

Pressure sensitivity of low permeability sandstones

Detailed core analysis has been carried out on 32 tight sandstones with permeabilities ranging over four orders of magnitude (0.0002 to 4.8 mD at 5000 psi confining pressure). Relationships between gas permeability and net confining pressure were measured for cycles of loading and unloading. For some samples, permeabilities were measured both along and across bedding planes. Large variations in stress sensitivity of permeability were observed from one sample to another. The ratio of permeability at a nominal confining pressure of 500 psi to that at 5000 psi was used to define a stress sensitivity ratio. For a given sample, confining pressure vs permeability followed a linear log-log relationship, the slope of which provided an index of pressure sensitivity. This index, as obtained for first unloading data, was used in testing relationships between stress sensitivity and other measured rock properties. Pressure sensitivity tended to increase with increase in carbonate content and depth, and with decrease in porosity, permeability and sodium feldspar. However, scatter in these relationships increased as permeability decreased. Tests for correlations between pressure sensitivity and various linear combinations of variables are reported. Details of pore structure related to diagenetic changes appears to be of much greater significance to pressure sensitivity than mineral composition.

Journal of Petroleum Science and Engineering↗
USGS2007

Methane gas hydrate effect on sediment acoustic and strength properties

To improve our understanding of the interaction of methane gas hydrate with host sediment, we studied: (1) the effects of gas hydrate and ice on acoustic velocity in different sediment types, (2) effect of different hydrate formation mechanisms on measured acoustic properties (3) dependence of shear strength on pore space contents, and (4) pore pressure effects during undrained shear. A wide range in acoustic p-wave velocities (V p ) were measured in coarse-grained sediment for different pore space occupants. V p ranged from less than 1 km/s for gas-charged sediment to 1.77–1.94 km/s for water-saturated sediment, 2.91–4.00 km/s for sediment with varying degrees of hydrate saturation, and 3.88–4.33 km/s for frozen sediment. V p measured in fine-grained sediment containing gas hydrate was substantially lower (1.97 km/s). Acoustic models based on measured V p indicate that hydrate which formed in high gas flux environments can cement coarse-grained sediment, whereas hydrate formed from methane dissolved in the pore fluid may not. The presence of gas hydrate and other solid pore-filling material, such as ice, increased the sediment shear strength. The magnitude of that increase is related to the amount of hydrate in the pore space and cementation characteristics between the hydrate and sediment grains. We have found, that for consolidation stresses associated with the upper several hundred meters of sub-bottom depth, pore pressures decreased during shear in coarse-grained sediment containing gas hydrate, whereas pore pressure in fine-grained sediment typically increased during shear. The presence of free gas in pore spaces damped pore pressure response during shear and reduced the strengthening effect of gas hydrate in sands.

Journal of Petroleum Science and Engineering↗
USGS2007

Characterization of methane hydrate host sediments using synchrotron-computed microtomography (CMT)

The hydrate-sediment interaction is an important aspect of gas hydrate studies that needs further examination. We describe here the applicability of the computed microtomography (CMT) technique that utilizes an intense X-ray synchrotron source to characterize sediment samples, two at various depths from the Blake Ridge area (a well-known hydrate-prone region) and one from Georges Bank, that once contained methane trapped as hydrates. Detailed results of the tomographic analysis performed on the deepest sample (667??m) from Blake Ridge are presented as 2-D and 3-D images which show several mineral constituents, the internal grain/pore microstructure, and, following segmentation into pore and grain space, a visualization of the connecting pathways through the pore-space of the sediment. Various parameters obtained from the analysis of the CMT data are presented for all three sediment samples. The micro-scale porosity values showed decreasing trend with increasing depth for all three samples that is consistent with the previously reported bulk porosity data. The 3-D morphology, pore-space pathways, porosity, and permeability values are also reported for all three samples. The application of CMT is now being expanded to the laboratory-formed samples of hydrate in sediments as well as field samples of methane hydrate bearing sediments.

Blake Ridge, Georges Bank↗
USGS2009

Geomechanical response of permafrost-associated hydrate deposits to depressurization-induced gas production

In this simulation study, we analyzed the geomechanical response during depressurization production from two known hydrate-bearing permafrost deposits: the Mallik (Northwest Territories, Canada) deposit and Mount Elbert (Alaska, USA) deposit. Gas was produced from these deposits at constant pressure using horizontal wells placed at the top of a hydrate layer (HL), located at a depth of about 900??m at the Mallik site and 600??m at the Mount Elbert site. The simulation results show that general thermodynamic and geomechanical responses are similar for the two sites, but with substantially higher production and more intensive geomechanical responses at the deeper Mallik deposit. The depressurization-induced dissociation begins at the well bore and then spreads laterally, mainly along the top of the HL. The depressurization results in an increased shear stress within the body of the receding hydrate and causes a vertical compaction of the reservoir. However, its effects are partially mitigated by the relatively stiff permafrost overburden, and compaction of the HL is limited to less than 0.4%. The increased shear stress may lead to shear failure in the hydrate-free zone bounded by the HL overburden and the downward-receding upper dissociation interface. This zone undergoes complete hydrate dissociation, and the cohesive strength of the sediment is low. We determined that the likelihood of shear failure depends on the initial stress state as well as on the geomechanical properties of the reservoir. The Poisson's ratio of the hydrate-bearing formation is a particularly important parameter that determines whether the evolution of the reservoir stresses will increase or decrease the likelihood of shear failure.

Journal of Petroleum Science and Engineering↗
USGS2019

An ANCOVA model for porosity and its uncertainty for oil reservoirs based on TORIS dataset

Porosity is one of the most important parameters to assess in-place oil or gas in reservoirs, and to evaluate recovery from enhanced production operations. Since it is relatively well-established to determine porosity using different laboratory and field methods, its value is usually determined at many locations across a reservoir as part of the common practice to capture reservoir heterogeneity and the variability in values. This suite of measurements and the distribution of values are most valuable for probabilistic reservoir assessments, and for spatial modeling if the exact data locations are known. Despite the importance of individual measurements to set the range of values for probabilistic studies, it is not always possible to access these data due to confidentiality. In most cases, commercial or publicly available databases that assessments may rely on usually report only mean values of porosity, like any other reservoir data, or they may not report a value at all. This makes both quantifying the mean value and the uncertainty around it difficult for probabilistic assessments. In this study, the TORIS (Tertiary Oil Recovery Information System) dataset of the National Petroleum Council and the U.S. Department of Energy was used to model porosity and the uncertainty around predicted values. TORIS is an integrated dataset of production data, reservoir properties, and project databases of crude oil reservoirs in the United States. The model presented in the paper was based on ANCOVA (Analysis of Co-Variance) of data from 1038 reservoirs from the TORIS dataset for porosity prediction, validation and testing for quantitative and qualitative parameters that may be readily available in most cases, and to estimate uncertainty around the mean values. This model also explored association of porosity values to different parameters, and to different depositional systems and diagenetic overprint conditions. Furthermore, an ANN (Artificial Neural Network) model was created to compare the predicted values of both models. Results showed that the ANN model was able to represent more of the variability, however it lacked the insights that might be gained from the ANCOVA model.

Journal of Petroleum Science and Engineering↗
USGS2020

Oil-source rock correlation studies in the unconventional Upper Cretaceous Tuscaloosa marine shale (TMS) petroleum system, Mississippi and Louisiana, USA

The U.S. Geological Survey assessed undiscovered unconventional hydrocarbon resources reservoired in the Upper Cretaceous Tuscaloosa marine shale (TMS) of southern Mississippi and adjacent Louisiana in 2018. As part of the assessment, oil-source rock correlations were examined in the TMS play area where operators produce light (38–45° API), sweet oil from horizontal, hydraulically-fractured wells in an overpressured ‘high-resistivity’ (>5 Ω-m) zone at the base of the TMS. Geochemical data from 39 oil samples and 17 source rock solvent extracts collected from the TMS play area indicate close correspondence for Tuscaloosa Group oils [from lower Tuscaloosa, middle Tuscaloosa (the TMS) and upper Tuscaloosa reservoirs] in thermal maturity (computed from MPI), SARA proportions, n- alkane distributions, isoprenoid and DBT/P ratios, monoaromatic steroids, and δ 13 C isotopic compositions (from whole oils, saturate and aromatic fractions). Other parameters (normal steranes, extended homohopanes, C 31 R/C 30 hopane, norhopane/hopane and tricyclic terpane ratios, gammacerane/hopane) show most oil samples have similar values, suggesting all Tuscaloosa Group oils are from a common mixed marine-terrigenous source rock. Tighter distributions for triaromatic steroid (TAS) and δ 13 C isotopic composition for conventional oils in lower and upper Tuscaloosa reservoirs may indicate charge occurred in a single or shorter pulse relative to TMS oils which show broader TAS and δ 13 C properties, possibly from their generation over an extended period of burial maturation. Dissimilarity in geochemical properties between lower Tuscaloosa source rock solvent extracts and Tuscaloosa Group oils indicates lower Tuscaloosa source rocks did not contribute significantly to conventional and unconventional Tuscaloosa Group hydrocarbon accumulations. Whereas, TMS solvent extracts are similar to Tuscaloosa Group oils, suggesting an oil-source rock correlation. Excluding the possibility for long-distance lateral migration from a similar source downdip (which is unnecessary given thermal maturity considerations), the observations indicate 1. the TMS is a self-sourced reservoir, 2. the TMS is the source of oils accumulated in nearby conventional Tuscaloosa Group reservoirs, and 3. thin organic-rich shales in the lower Tuscaloosa did not contribute substantially to any oil accumulations in the Tuscaloosa Group.

Louisiana, Mississippi↗
USGS1998

An improved technique for modeling initial reservoir hydrocarbon saturation distributions: Applications in Illinois (USA) aux vases oil reservoirs

An improved technique for modeling the initial reservoir hydrocarbon saturation distributions is presented. In contrast to the Leverett J-function approach, this methodology (hereby termed flow-unit-derived initial oil saturation or FUSOI) determines the distributions of the initial oil saturations from a measure of the mean hydraulic radius, referred to as the flow zone indicator (FZI). FZI is derived from porosity and permeability data. In the FUSOI approach, capillary pressure parameters, S(wir), P(d), and ??, derived from the Brooks and Corey (1966) model [Brooks, R.H., Corey, A.T., 1966. Hydraulic properties of porous media, Hydrology Papers, Colorado State Univ., Ft. Collins, No. 3, March.], are correlated to the FZI. Subsequent applications of these parameters then permit the computation of improved hydrocarbon saturations as functions of FZI and height above the free water level (FWL). This technique has been successfully applied in the Mississippian Aux Vases Sandstone reservoirs of the Illinois Basin (USA). The Aux Vases Zeigler field (Franklin County, IL, USA) was selected for a field-wide validation of this FUSOI approach because of the availability of published studies. With the initial oil saturations determined on a depth-by-depth basis in cored wells, it was possible to geostatistically determine the three-dimensional (3-D) distributions of initial oil saturations in the Zeigler field. The original oil-in-place (OOIP), computed from the detailed initialization of the 3-D reservoir simulation model of the Zeigler field, was found to be within 5.6% of the result from a rigorous material balance method.An improved technique for modeling the initial reservoir hydrocarbon saturation distributions is presented. In contrast to the Leverett J-function approach, this methodology (hereby termed flow-unit-derived initial oil saturation or FUSOI) determines the distributions of the initial oil saturations from a measure of the mean hydraulic radius, referred to as the flow zone indicator (FZI). FZI is derived from porosity and permeability data. In the FUSOI approach, capillary pressure parameters, Swir, Pd, and ??, derived from the Brooks and Corey (1966) model, are correlated to the FZI. Subsequent applications of these parameters then permit the computation of improved hydrocarbon saturations as functions of FZI and height above the free water level (FWL). This technique has been successfully applied in the Mississippian Aux Vases Sandstone reservoirs of the Illinois Basin (USA). The Aux Vases Zeigler field (Franklin County, IL, USA) was selected for a field-wide validation of this FUSOI approach because of the availability of published studies. With the initial oil saturations determined on a depth-by-depth basis in cored wells, it was possible to geostatistically determine the three-dimensional (3-D) distributions of initial oil saturations in the Zeigler field. The original oil-in-place (OOIP), computed from the detailed initialization of the 3-D reservoir simulation model of the Zeigler field, was found to be within 5.6% of the result from a rigorous material balance method.

Journal of Petroleum Science and Engineering↗
USGS2024

Characterization of the structural–stratigraphic and reservoir controls on the occurrence of gas hydrates in the Eileen Gas Hydrate Trend, Alaska North Slope

One of the most studied permafrost-associated gas hydrate accumulations in Arctic Alaska is the Eileen Gas Hydrate Trend. This study provides a detailed re-examination of the Eileen Gas Hydrate Trend with a focus on the gas hydrate accumulation in the western part of the Prudhoe Bay Unit. This integrated analysis of downhole well log data and published geophysical data has provided new insight on structural, stratigraphic, and reservoir controls on the occurrence of gas hydrates in the Eileen Gas Hydrate Trend. This study revealed the relatively complex nature of the gas hydrate occurrences in the Eileen Gas Hydrate Trend, with gas hydrates present in a series of coarsening upward, laterally pervasive, mostly fine-grained sand beds exhibiting high gas hydrate saturations. Most of the gas hydrate-bearing reservoirs in the Eileen Gas Hydrate Trend are laterally segmented into distinct northwest- to southeast-trending fault blocks, occur in a combination of structural–stratigraphic traps, and are only partially hydrate filled with distinct down-dip water contacts. These findings suggest that the traditional parts of a petroleum system (i.e., reservoir, gas source, gas migration, and geologic timing of the system formation) also control the occurrence of gas hydrates in the Eileen Gas Hydrate Trend.

Alaska↗
USGS2016

Evaluation of gas production potential from gas hydrate deposits in National Petroleum Reserve Alaska using numerical simulations

An evaluation of the gas production potential of Sunlight Peak gas hydrate accumulation in the eastern portion of the National Petroleum Reserve Alaska (NPRA) of Alaska North Slope (ANS) is conducted using numerical simulations, as part of the U.S. Geological Survey (USGS) gas hydrate Life Cycle Assessment program. A field scale reservoir model for Sunlight Peak is developed using Advanced Processes & Thermal Reservoir Simulator (STARS) that approximates the production design and response of this gas hydrate field. The reservoir characterization is based on available structural maps and the seismic-derived hydrate saturation map of the study region. A 3D reservoir model, with heterogeneous distribution of the reservoir properties (such as porosity, permeability and vertical hydrate saturation), is developed by correlating the data from the Mount Elbert well logs. Production simulations showed that the Sunlight Peak prospect has the potential of producing 1.53 × 10 9 ST m 3 of gas in 30 years by depressurization with a peak production rate of around 19.4 × 10 4 ST m 3 /day through a single horizontal well. To determine the effect of uncertainty in reservoir properties on the gas production, an uncertainty analysis is carried out. It is observed that for the range of data considered, the overall cumulative production from the Sunlight Peak will always be within the range of ±4.6% error from the overall mean value of 1.43 × 10 9 ST m 3 . A sensitivity analysis study showed that the proximity of the reservoir from the base of permafrost and the base of hydrate stability zone (BHSZ) has significant effect on gas production rates. The gas production rates decrease with the increase in the depth of the permafrost and the depth of BHSZ. From the overall analysis of the results it is concluded that Sunlight Peak gas hydrate accumulation behaves differently than other Class III reservoirs (Class III reservoirs are composed of a single layer of hydrate with no underlying zone of mobile fluids) due to its smaller thickness and high angle of dip.

Alaska↗