Showing papers on "Petroleum reservoir published in 2022"

Reservoir quality discrimination of the Albian-Cenomanian reservoir sequences in the Ivorian basin: a lithological and petrophysical study

Abstract: The Albian-Cenomanian reservoirs of the Ivorian sedimentary basin consist mainly of conglomeratic, pebbly, and very fine to coarse-grained sandstones. In the present study, the lithologic composition, flow and storage capacities, and reservoir quality parameters were studied in detail. Some fresh, clean and non-fractured samples were selected representative from FE-1 well in the depocenter of the basin, FE-2 well to the west, and FE-3 well to the east of the basin. Lithologic studies indicated that heterogeneity increases greatly to the east due to the implementation of diagenetic factors including cementation, silicification, authigenic clay minerals, and compaction. Though of the dominant reservoir quality-reducing factors, to the east, the reservoir quality increases due to increasing the grain size and the interstitial pore types. Porosity and permeability of samples were estimated by helium and nitrogen injection, respectively, whereas the reservoir quality was measured using different techniques, e.g., the FZI (flow zone indicator), the RQI (reservoir quality index), the effective pore radius (R35) of Winland, and the DRT (discrete rock type). The reservoir quality properties declared that the present plug samples can be clustered into six RRTs (reservoir rock types), with increasing reservoir quality from RRT6 (conglomeratic sandstone lithofacies) to RRT1 (deformed sandstone lithofacies).

Petrophysical core-based zonation of OW oilfield in the Bredasdorp Basin South Africa

Abstract: This study aims to generate rock units based on core permeability and porosity of OW oilfield in the Bredasdorp Basin offshore South Africa. In this study, we identified and classified lithofacies based on sedimentology reports in conjunction with well logs. Lucia's petrophysical classification method is used to classify rocks into three classes. Results revealed three lithofacies as A (sandstone, coarse to medium-grained), B (fine to medium-grained sandstone), and C (carbonaceous claystone, finely laminated with siltstone). Lithofacies A is the best reservoir quality and corresponds to class 1, while lithofacies B and C correspond to class 2 and 3, which are good and poor reservoir quality rock, respectively. An integrated reservoir zonation for the rocks is based on four different zonation methods (Flow Zone indicator (FZI), Winland r35, Hydraulic conductivity (HC), and Stratigraphy modified Lorenz plot (SMLP)). Four flow zones Reservoir rock types (RRTs) were identified as RRT1, RRT3, RRT4, and RRT5, respectively. The RRT5 is the best reservoir quality composed of a megaporous rock unit, with an average FZI value between 5 and 10 µm, and HC from 40 to 120 mD/v3, ranked as very good. The most prolific flow units (RRT5 and RRT4 zones) form more than 75% of each well's flow capacities are supplied by two flow units (FU1 and FU3). The RRT1 is the most reduced rock quality composed of impervious and nanoporous rock. Quartz is the dominant framework grain, and siderite is the dominant cement that affects flow zones. This study has demonstrated a robust approach to delineate flow units in the OW oilfield. We have developed a useful regional petrophysical reservoir rock flow zonation model for clastic reservoir sediments. This study has produced, for the first time, insights into the petrophysical properties of the OW oilfield from the Bredasdorp Basin South Africa, based on integration of core and mineralogy data. A novel sandstone reservoir zonation classification criteria developed from this study can be applied to other datasets of sandstone reservoirs with confidence.

Decoding of seismic data for complex stratigraphic traps revealing by seismic attributes analogy in Yidma/Alamein concession area Western Desert, Egypt

Abstract: Abstract Sandstone channels are one of the best stratigraphic traps for hydrocarbon accumulation, and their depositional and composition make them difficult to detect on ordinary seismic data, especially in structurally affected onshore areas like the Western Desert of Egypt. The Western Desert of Egypt has many hydrocarbon-bearing reservoirs of various compositions like carbonates and sandstones with high production rates, and thus the Western Desert of Egypt is recognized as a hot spot for oil and gas exploration. One of the important reservoirs in the Lower Cretaceous “the Aptian sand” produced around 285 MBBLS cumulative oil of 22° API and still produces 102 BOPD. This reservoir has a channel-type depositional environment, and the dimensions of this channel could be resolved by good quality 3D seismic data in the moderately deep basins as the basins become deeper, the detection of the channel becomes increasingly challenging. This study aims to delineate the geometry of this reservoir and reveal the exposure from the Aptian sand channel in the Alamein area using the seismic attributes analogy on the re-processed 3D seismic data to determine the best drilling location for increasing the production from this reservoir. In this context, the relative acoustic impedance (RAI), iso-frequency components, and sweetness stratigraphic attribute analyses were conducted on the optimized seismic data and attested as important as they resolved the stratigraphic geological mystery in the structurally affected study area. These attribute analyses revealed the exposure from the distinctive meander channel of the Aptian sand for the first time in the study area nearby the producing Alamein field, where this channel was hard to be distinguished by the ordinary seismic interpretation methods and there is no drilled well penetrated the detected channel’s body. Upon the results, the conclusion and recommendation summaries to intensify the efforts to test the productivity of the detected channel to increase the production from this motivating reservoir by drilling a new well targeting the best structural locations of the channel body.

Petrophysical analysis of well logs and core samples for reservoir evaluation: a case study of southern Issaran Field, Gulf of Suez province, Egypt

Abstract: Abstract Understanding basic petrophysical properties may enhance the recovery of residual oil saturation and help in reservoir management. Reservoir oil saturation is the fraction of the porosity of a zone occupied by oil. The trapping may increase with the increase of porosity. Oil reservoirs represent a significant fraction of the reservoirs in the world-wide. We try to make a reservoir evaluation using petrophysical analysis of well logs and core samples at Issaran Field, South Gharib Formation, West of the Gulf of Suez, southeast Egypt. This area was heavily influenced by the structural setting of the Gulf of Suez’s central province, which is characterized by major SW dipping faults with a regional stratigraphic dip toward the NE. The high structural blocks are located in the center of the research area, and the low structural region is located in the southwest. South Gharib Formation is primarily composed of carbonates with few sulfates that grade upwards into sulfate-rich beds in the upper part. Laminated dolomitic limestone, with evaporites grades, changes downward into laminated dolomitic limestone and marly limestone, in the lower part. The anhydrite and dolomite units near the bottom have spotty oil stains. The structural setup is continued by the spread and deposition of this formation. We try to make analytical examination, of some reservoirs, accomplished by analyzing both well log data and core rock samples, vertically and laterally. According to the study of the horizontal permeability to vertical permeability ratio (Permeability anisotropy; $$\lambda_{k}$$ λ k ), the reservoir is laminated rock ( $$\lambda_{k} = 1.1 - 5$$ λ k = 1.1 - 5 ), with a few data samples nearly isotropic ( $$\lambda_{k} = {1 \mathord{\left/ {\vphantom {1 {1.1}}} \right. \kern- ulldelimiterspace} {1.1}}$$ λ k = 1 / 1.1 –1.1) and fractured ( $$\lambda_{k} = {1 \mathord{\left/ {\vphantom {1 {2.5}}} \right. \kern- ulldelimiterspace} {2.5}}$$ λ k = 1 / 2.5 –1/1.1). Reservoir data histograms show that the most typical values of the data are 20–30% oil saturation and 7–10% porosity. The net-pay zone varies from four to 71 feet at different depths (897–1414 feet). Due to low shale content, water saturation, high effective porosity values, hydrocarbon saturation, may show higher net-pay thickness. These results may help to enhance the oil recovery. The area in the middle of the research area is suggested for future hydrocarbon development and using more petrophysical analysis.

Acoustic, density, and seismic attribute analysis to aid gas detection and delineation of reservoir properties

Abstract: Banner headline This chapter reviews multiple applications of seismic attributes in reservoir characterization of natural gas reservoirs. Some seismic attributes such as bright spots, flat spots, dim spots, and polarity changes provide direct gas indicators. Other attributes can be formulated to indicate reservoir rock and fluid properties. Abstract Seismic attributes play a pivotal role in the detection and delineation of natural gas reservoirs. Through integration with core and well log derived data, seismic attributes have been very successful in rock and fluid properties mapping. Some seismic attributes such as bright spots, flat spots, dim spots, polarity changes and AVO inversion attributes are direct gas indicators. Some attributes such as inverted acoustic impedance (AI) have strong relationships with elastic moduli and petrophysical data such as porosity, water saturation and lithology. Accordingly, fluid and rock properties of natural gas reservoirs can be formulated to a set of predefined seismic attributes using statistical or machine learning techniques. This chapter reviews multiple applications of seismic attributes and their combination in reservoir characterization of natural gas reservoirs. Several examples and case studies of their practical implementation in fluid typing and rock properties estimation are provided. Seismic attributes effectively aid the exploration and development of natural gas reservoirs. Through integration with well data, they help reduce uncertainty in reservoir static and dynamic simulation models and much more successful implantation of field development plans.

Study on fluid mobility in sandwich-type shale oil reservoir using two-dimensional nuclear magnetic resonance approaches

Abstract: ABSTRACT Regarding sandwich-type shale oil reservoir characterized by diversified lithologies and complex fluid mobility, we combined one- and two-dimensional (1D and 2D) nuclear magnetic resonance (NMR) core analysis techniques to quantitatively study the movable oil and fluid saturations of rock samples with different lithologies. First, we used 2D T1-T2 NMR to analyze the spectrum curve of the dolomitic mudstone and siltstone samples from a sandwich-type shale oil reservoir at initial and oil-saturated states. We evaluated the occurrence of movable oil saturations in source and reservoir rocks. Then, we analyzed samples of the siltstone serving as the reservoir rock using a centrifuge combined with 1D NMR approach to evaluate the characteristics of movable fluid saturations inside the reservoir. The results showed that the samples of dolomitic mudstone serving as the source rock in the sandwich-type shale oil reservoir in the Lucaogou Formation in Jimsar had the occurrence of kerogen and bitumen signals, the development of small- and medium-scale organic matter pores, and an average movable oil saturation of 15.6%. The siltstone serving as the reservoir rock had an average movable oil saturation of 53.8%, and its movable fluid saturation was positively correlated with porosity and permeability. For samples whose porosity was greater than 12% and permeability was greater than 0.1 mD, their movable fluid saturations usually were higher than 40%. Therefore, siltstone was the preferable diagenetic facies for the development of high-quality reservoirs.

A New Method for Determination of Rock Fabric Number from Well Logs in Unconventional Tight Oil Carbonates

Abstract: This paper develops a new method for estimation of rock fabric number (RFN) from well logs in unconventional tight oil carbonates with less than 0.1 md. The objective is to investigate the oil potential of a Middle Cretaceous tight carbonate in Mexico. Development of a method for these conditions is challenging as the current approach developed by Lucia (1983) has been explained for carbonates with more than 0.1md. The method is calibrated with data from cores and cuttings and allows estimating the presence of grainstone, packstone and wackstone rocks in unconventional tight carbonates from well logs. A crossplot of RFN vs rp35 (pore throat radius at 35% cumulative pore volume) permits delimiting intervals with good production potential that is supported by well testing data. Information for analysis of the Mexican carbonate comes from well logs of 9 wells and 2 re-entry wells, four buildup tests and a limited amount of core and drill cuttings information. All data were provided by a petroleum company and have been used, for transparency, without any modifications. An unconventional tight carbonate as defined in this paper has a permeability smaller than 0.1 md. The unconventional tight oil carbonate reservoir considered in this study includes 95 percent of data with permeabilities smaller than 0.1 md and only 5% with permeabilities larger than 0.1 md. The method introduced by Lucia (1983) and Jennings and Lucia (2003) for determining RFN is powerful, but they explained it only for permeabilities larger than 0.1 md. Thus, the need for a methodology that allows estimating from well logs the presence of grainstone, packstone and/or wackstone in unconventional tight carbonate reservoirs with permeabilities smaller than 0.1 md. Results indicate that the RFN provides a useful approach for distinguishing grainstone, packstone and wackstone rocks in unconventional tight carbonate reservoirs. Furthermore, rock fabric can be linked with Pickett plots to provide an integrated quantitative evaluation of RFN, porosity, water saturation, permeability, pore throat radius, and capillary pressure. This integration indicates that there is good oil potential in the Middle Cretaceous unconventional tight carbonate in Mexico. The novelty of this paper is the use of rock fabric (RFN) in unconventional tight carbonates with permeabilities smaller than 0.1 md for estimating the presence of grainstone, packstone and wackstone rocks from well logs. In addition, a crossplot of RFN vs rp35 provides a good indication of intervals with oil production potential.

Improved Amott Cell Procedure for Predictive Modeling of Oil Recovery Dynamics from Mixed-Wet Carbonates

Abstract: Spontaneous counter-current imbibition in Amott cell experiments is a convenient laboratory method of studying oil recovery from oil-saturated rock samples in secondary or tertiary oil recovery by waterflood of adjustable composition. Classical Amott cell experiment estimates ultimate oil recovery. It is not designed, however, for studying the dynamics of oil recovery. In this work we identify a flaw in the classical Amott cell imbibition experiments that hinders the development of predictive recovery models for mixed-wet carbonates. We revise the standard Amott procedure in order to produce smoother experimental production curves, which then can be described by a mathematical model more accurately. We apply Generalized Extreme Value distribution to model the cumulative oil production. We start with the Amott imbibition experiments and scaling analysis for Indiana limestone core plugs saturated with mineral oil. The knowledge gained from this study will allow us to develop a predictive model of water-oil displacement for reservoir carbonate rock and crude oil recovery systems.

Application of Machine Learning for Mineralogy Prediction from Well Logs in the Bakken Petroleum System

Abstract: One of the significant unconventional oil reserves in the USA is the Bakken Petroleum System located in the Williston Basin. It is known for its complex lithology, composed of three prominent members, Upper and Lower Bakken, with similar properties of organic-rich shale relatively uniform compared to the middle member with five distinct lithofacies, formed mainly from calcite, dolomite, or silica. The higher properties variability makes the reservoir characterization more challenging with low permeability and porosity. Understanding lithology by quantifying mineralogy is crucial for accurate geological modeling and reservoir simulation. Besides that, the reservoir’s capacity and the oil production are affected by the type and the mineral volume fractions, which impact the reservoir properties. Conventionally, to identify the mineralogy of the reservoir, the laboratory analysis (X-Ray Diffraction, XRD) using core samples combined with the well logs interpretation is widely used. The unavailability of the core data due to the high cost, as well as the discontinuities of the core section of the reservoir due to the coring failures and the destructive operations, are one of the challenges for an accurate mineralogy quantification. The XRD cores analysis is usually used to calibrate the petrophysical evaluation using well logs data because they are economically efficient. To remedy to these limitations, artificial intelligence and data-driven based models have been widely deployed in the oil and gas industry, particularly for petrophysical evaluation. This study aims to develop machine learning models to identify mineralogy by applying six different machine learning methods and using real field data from the upper, middle, and lower members of the Bakken Formation. Efficient pre-processing tools are applied before training the models to eliminate the XRD data outliers due to the formation complexity. The algorithms are based on well logs as inputs such as Gamma Ray, bulk density, neutron porosity, resistivity, and photoelectric factor for seven (07) wells. XRD mineral components for 117 samples are considered outputs (Clays, Dolomite, Calcite, Quartz, and other minerals). The results' validation is based on comparing the XRD Data prediction from the developed models and the petrophysical interpretation. The applied approach and the developed models have proved their effectiveness in predicting the XRD from the Bakken Petroleum system. The Random Forest Regressor delivered the best performance with a correlation coefficient of 78 percent. The rest of the algorithms had R-scores between 36 and 72 percent, with the linear regression having the lowest coefficient. The reason is the non-linearity between the inputs and outputs.

Integrated Field Development Modelling to Improve Recovery from a Complex Fractured Carbonate Reservoir with Potential for Low Salinity Waterflooding EOR

Abstract: Integrated field development studies were performed to increase oil recovery from the Marrat reservoir in the Umm Gudair field, a large, low permeability, complex, naturally fractured and highly faulted carbonate reservoir. The studies involved rebuilding the static model, creating and history matching a new dynamic model and using it to examine redevelopment scenarios. These included well interventions and workovers under primary depletion, secondary waterflood and, following a screening exercise, low salinity flooding (LSF). A new structural interpretation of 3D seismic data provided a revised static geological model and yielded insight into the number, geometry and origin of the many faults intersecting the reservoir. Rock types defined from core analysis were distributed in the static geological model using trends from Bayesian lithofacies classification based on pre-stack inversion of seismic data. Porosity and permeability were modelled by rock type. Saturation-height functions for each rock type were developed from mercury injection capillary pressure (MICP) data; and the reservoir free water level was varied so that these functions honoured the log-based water saturation interpretation. The dynamic model input description was based on available and interpreted data for the assumed oil wet reservoir. The history matching was aided by sophisticated application of decline curve analysis (DCA) and used an Opportunity Index approach to optimise well placement. The history matching led to a simplified and effective solution for characterising the locally naturally fractured reservoir nature. The effect of high permeabilities associated with increased fracture density was accommodated by introducing facies-based and distance from fault-related permeability modifiers, while maintaining geological rigour. The dynamic model was used to examine a range of field redevelopment scenarios. This showed that LSF could enhance field recovery and achieve a three-fold increase in estimated ultimate recovery, in conjunction with other improved reservoir management strategies. The results provided support for specialised laboratory and dynamic modelling investigations as a precursor to LSF pilot trials. A low cost source of LSF injectant was identified which could contribute to lowering the overall carbon footprint.

Secondary and Tertiary Oil Recovery Processes

Abstract: The demand for crude oil is continuously increasing every year, and the discovery of new oil reservoirs is declining. Crude oil recovery from the mature and developed fields is somewhere between 20 and 40% of the original oil in place. Therefore, it is necessary to boost the production from the existing mature fields. Secondary recovery of hydrocarbon involves techniques that compensate the natural energy of the reservoir by injecting fluids, usually water or gas. Tertiary recovery methods are implemented to recover the crude oil trapped within the capillaries of the reservoir rocks. Tertiary recovery is the process in which different combinations of chemicals or thermal energy, or microbes are infused into the reservoir, which alters the reservoir rock and fluid properties, relative permeability, capillary pressure within the porous medium, interfacial tension, and wettability to recover crude oil and helps in additional crude oil recovery. The mechanism involved in the process and the selection of secondary and tertiary oil recovery methods are discussed in this chapter with a brief introduction of core flooding experiments and reservoir simulators.

Image log analysis of Asmari reservoir fractures in a Southwest Iranian oil field

Abstract: Research on petroleum structures necessitates the investigation of reservoir rock fractures during field production and development phases and the use of software specifically designed for reservoirs. The present research aims to systematically investigate fractures in the Asmari reservoir, how these fractures develop using FMS and FMI image logs, and the effect of these fractures on the porosity and permeability of these reservoirs. The results indicate the viability of these logs as tools for detecting fractures and structural reservoir dips where water-based drilling mud is used. The present research incorporates the results obtained from FMI interpretations of two wells in the field under study for comparison. In general, production in the Asmari reservoir relies on a combination of fractures and rock matrices. Fractures and porous zones have a substantial effect on the properties of the reservoir rock. Also, two general patterns of tectonic fractures from longitudinal and oblique folding, as well as various other fractures arising from faulting, can be observed in this reservoir. Of these folds, the longitudinal pattern is the most frequent, as it forms the most open fractures extending to N35–65 W. These fractures are primarily observed in the Asmari higher zones (particularly Zone 1).