Academic literature on the topic 'Net reservoir porosity thickness product'
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Journal articles on the topic "Net reservoir porosity thickness product"
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An, P., W. M. Moon, and F. Kalantzis. "Reservoir characterization using seismic waveform and feedforword neural networks." GEOPHYSICS 66, no. 5 (September 2001): 1450–56. http://dx.doi.org/10.1190/1.1487090.
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Feedforward neural networks are used to estimate reservoir properties. The neural networks are trained with known reservoir properties from well log data and seismic waveforms at well locations. The trained neural networks are then applied to the whole seismic survey to generate a map of the predicted reservoir property. Both theoretical analysis and testing with synthetic models show that the neural networks are adaptive to coherent noise and that random noise in the training samples may increase the robustness of the trained neural networks. This approach was applied to a mature oil field to explore for Devonian reef‐edge oil by estimating the product of porosity and net pay thickness in northern Alberta, Canada. The resulting prediction map was used to select new well locations and design horizontal well trajectories. Four wells were drilled based on the prediction; all were successful. This increased production of the oil field by about 20%.
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ALhakeem, Naseem Sh, Medhat E. Nasser, and Ghazi H. AL-Sharaa. "3D Geological Modeling for Yamama Reservoir in Subba, Luhias and Ratawi Oil Fields, South of Iraq." Iraqi Journal of Science 60, no. 5 (May 26, 2019): 1023–36. http://dx.doi.org/10.24996/ijs.2019.60.5.12.
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3D geological model for each reservoir unit comprising the Yamama Formation revealed to that the formation is composed of alternating reservoirs and barriers. In Subba and Luhais fields the formation began with barrier YB-1 and four more barriers (YB-2, YB-3, YB-4, YB-5), separated five reservoirs (YR-A, YR-B, YR-C, YR-D, YR-E) ranging in thickness from 70 to 80 m for each of them deposited by five sedimentary cycles. In the Ratawi field the formation was divided into three reservoir units (YR-A, YR-B, and YR-C) separated by two barrier units (YB-2 and YB-3), the first cycle is missing in Ratawi field.
The study involves 1 well in Luhais field (Lu-12), 3 wells in Subba field (Su-7, Su-8, and Su-9), and 5 wells in Ratawi field (Rt-3, Rt-4, Rt-5, Rt-6 and Rt-7), the Luhais, Subba, and Ratawi fields located in the Mesopotamia zone (Zubair subzone).
The reservoir units (YR-C and YR-D) in Subba oil field, and YR-B in Ratawi oil field represent the major reservoir units that characterized by the best Petrophysical properties (the highest porosity, the lowest water saturation, and the best Net Pay Thickness), Luhais oil field has poor to moderate Petrophysical properties and low oil bearing in YR-A, YR-B and YR-C units, and produce heavy oil and salt water from YR-D and YR-E as indicated by low resistivity log reading, and according to the Drill Steam Test (DST) with the description of cutting in final geological reports.
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Sarhan, Mohammad Abdelfattah. "Petrophysical characterization for Thebes and Mutulla reservoirs in Rabeh East Field, Gulf of Suez Basin, via well logging interpretation." Journal of Petroleum Exploration and Production Technology 11, no. 10 (September 6, 2021): 3699–712. http://dx.doi.org/10.1007/s13202-021-01288-x.
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AbstractThe current work assesses the sandstones of the Mutulla Formation as well as the limestone of the Thebes Formation for being promising new oil reservoirs in Rabeh East field at the southern portion of the Gulf of Suez Basin. This assessment has been achieved through petrophysical evaluation of wireline logs for three wells (RE-8, RE-22 and RE-25). The visual analysis of well logs data revealed that RE-25 Well is the only well demonstrating positive criteria in five zones for being potential oil reservoirs. The favourable zone within Thebes Formation locates between depths 5084 ft and 5100 ft (Zone A). However, the other positive zones in Mutulla Formation occur between depths: 5403.5–5413.5 ft (Zone B), 5425.5–5436 ft (Zone C), 5488–5498 ft (Zone D) and 5558.5–5563.5 ft (Zone E). The quantitative evaluation shows that the Zone A of Thebes Formation is the best oil-bearing zone in RE-25 Well in terms of reservoir quality since it exhibits lowest shale volume (0.07), minimum water saturation (0.23) and lowest bulk volume of water (0.03). These limestone beds include type of secondary porosity beside the existing primary porosity. On the other hand, the sandstones of Mutulla Formation in RE-25 contain four reservoir zones (B, C, D and E) with the total net pay thickness of 35.5 ft. Moreover, the obtained results revealed that it is expected for zones B, C and D to produce oil without water but Zone E will produce oil with water.
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Vargo, Jay, Jim Turner, Vergnani Bob, Malcolm J. Pitts, Kon Wyatt, Harry Surkalo, and David Patterson. "Alkaline-Surfactant-Polymer Flooding of the Cambridge Minnelusa Field." SPE Reservoir Evaluation & Engineering 3, no. 06 (December 1, 2000): 552–58. http://dx.doi.org/10.2118/68285-pa.
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Summary The Cambridge Minnelusa field alkaline-surfactant-polymer (ASP) flood was an economic and technical success, with ultimate incremental oil of 1,143,000 bbl at a cost of $2.42 per barrel. This success was due to an integrated approach of the application, including: reservoir engineering and geologic studies, laboratory chemical system design, numerical simulation, facilities design, and ongoing monitoring. This paper discusses how each of these was used in the design and evaluation of the Cambridge ASP project. Introduction The purpose of the alkaline-surfactant-polymer technology is to produce incremental oil by reducing the waterflood residual oil saturation. The technology combines interfacial tension-reducing chemicals (alkali and surfactant) with a mobility control chemical (polymer). The interfacial tension reducing chemicals minimize the capillary forces that trap waterflood residual oil while the mobility control chemical improves reservoir contact and flood efficiency. The first alkaline-surfactant-polymer project was performed in a nearby Minnelusa field.1,2 Other alkaline-surfactant-polymer projects include a pilot in an Oklahoma field,3 and three in People's Republic of China oil fields.4–9 Lessons learned from these projects and applied to the Cambridge alkaline-surfactant-polymer project are: good mobility control is essential for a successful project; a detailed study of the reservoir including geology, reservoir engineering, laboratory fluid design, and numerical simulation improve the probability of success; injection facilities must mix the injected solution according to the design parameters for a successful project; and attention to detail, including quality control of injected materials and scheduled maintenance of injection and mixing equipment, is important. The Cambridge field, located in Section 28 of Township 53N and Range 68W in Crook County, Wyoming, is operated by Plains Petroleum Operating Co., a subsidiary of Barrett Resources Corp. The field produces 31 cp, 20° API gravity crude oil from the Permian Minnelusa upper "B" sand at 2139 m [7,108 ft]. The reservoir temperature is 55.6°C [132°F] and the average thickness is 8.75 m [28.7 ft]. The crude oil formation volume factor is 1.03 with a bubblepoint of 586 kPa [85 psi]. The average porosity and permeability are 18% and 0.834 µm2 [845 md], respectively. Connate water saturation was 31.6% with an initial reservoir pressure of 12 355 kPa [1792 psi]. Field History The Cambridge field is defined as 1 131 500 m3 [7,117 Mbbl] pore volume with 795 000 STm3 [4,875 MSTB] of original oil in place. The field was discovered by McAdams, Roux, and Associates in 1989 with the MRA Federal 31-28. All subsequent drilling locations were based on three-dimensional (3D) seismic data. Peak primary oil production was 77.7 m3/d [489 BOPD]. Within a year, the production rate declined to 5.9 m3/d [37 BOPD], as is typical of Minnelusa reservoirs. The producing mechanism is fluid and rock expansion with the initial gas-oil ratio (GOR) being essentially zero. The Federal 21-28 and 32-28 began production in June 1990 with peak production of 11.0 and 46.4 m3/d [69 and 292 BOPD], respectively. Federal 23-28 started production in October 1990 with peak production occurring in November 1990 of 33.7 m3/d [212 BOPD] of oil and 2.9 m3/d [18 BWPD] of water. Primary production was 34 600 m3 [217.7 Mbbl] oil and 3800 m3 [23.3 Mbbl] water from December 1989 to January 1993. Water injection began in January 1993 with the conversion of the Federal 32-28. Alkaline-surfactant-polymer solution injection started one month later in February 1993. Therefore, the alkaline-surfactant-polymer process was applied as a secondary flood. As a result, operating costs are not duplicated by running a waterflood followed by an alkaline-surfactant-polymer flood. The polymer drive solution began injection in October 1996 with the final water drive beginning in May 2000. The chemical injection sequence was: 30.7% Vp of alkaline-surfactant-polymer solution followed by 29.7% Vp of polymer drive solution followed by water to the economic limit. Percent pore volume is based on swept area pore volume. Swept area is defined as the volume of reservoir contacted by the injected fluid and is approximately 82% of the total pore volume for the Cambridge field. Swept area injected volume and oil recovery calculations are more comparable to radial coreflood results than total field values. For reservoirs like the Minnelusa in which well placement is limited by reservoir geometry, comparison of total field calculations can be misleading. Differences in total field calculations are often dictated by reservoir contact inefficiency and not process efficiency. When this condition exists, swept area calculation is a better comparison to delineate accurately the economic injected chemical volumes and oil recovery. 10 The calculated swept area pore volume is 926 400 m 3 [5,827 Mbbl] and the original oil in place is 647 300 m3 [4,071.8 Mbbl]. Interpretation of 3D seismic data resulted in the drilling of the Federal 41A-28 in November 1994 and the Federal 33-28 in February 1996. Federal 41A-28 was produced through March 1996 and Federal 33-28 was produced through October 1998. Geologic Description The Cambridge field is on the eastern flank of the Powder River basin and produces oil from the Permian Minnelusa upper B sandstone. The Minnelusa formation is unconformably overlain in this area by the Opeche siltstone member of the Permian Goose Egg formation, which in turn is overlain by the regional Minnekahta limestone, also a member of the Goose Egg formation. The Minnelusa vertical sequence consists of alternating carbonates and sandstones. The Minnelusa upper B reservoir is a friable, Eolian sandstone with modest amounts of dolomite and anhydrite cement and is a preserved remnant of a highly dissected coastal dune complex. Dolomite and anhydrite cement are the main chemical adsorbing sites of the Cambridge sand. Fig. 1 depicts the field's net-pay isopach. The reservoir dips approximately 1.7° to the southwest. A water-oil contact controls the field's producing limit on the southwest. Dystra-Parsons is 0.57. Preferential flow of injected fluids follows an axis along Wells 41A-28 and 21-28. The 3D seismic indicates the sand thins between Wells 33-28 and 23-28.
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Neff, Dennis B. "Amplitude map analysis using forward modeling in sandstone and carbonate reservoirs." GEOPHYSICS 58, no. 10 (October 1993): 1428–41. http://dx.doi.org/10.1190/1.1443358.
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The extent to which seismic amplitude maps can contribute to the analysis of hydrocarbon reservoirs was investigated for clastic and carbonate reservoirs worldwide. By using a petrophysical‐based, forward modeling process called incremental pay thickness (IPT) modeling, five lithology types were quantitatively analyzed for the interplay of seismic amplitude versus lithology, porosity, hydrocarbon pore fluid saturation, bedding geometries, and reservoir thickness. The studies identified three common tuning curve shapes (concave, convex, and bilinear) that were primarily dependent upon the lithology model type and the average net porosity therein. While the reliability of pay and porosity predictions from amplitude maps varied for each model type, all analyses showed a limited thickness range for which amplitude data could successfully predict net porosity thickness or hydrocarbon pore volume. The investigation showed that systematic forward modeling is required before amplitude maps can be properly interpreted.
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Neff, Dennis B. "Incremental pay thickness modeling of hydrocarbon reservoirs." GEOPHYSICS 55, no. 5 (May 1990): 556–66. http://dx.doi.org/10.1190/1.1442867.
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The one-dimensional convolution model or synthetic seismogram provides more information about the seismic waveform expression of hydrocarbon reservoirs when petrophysical data (porosity, shale volume, water saturation, etc.) are systematically integrated into the seismogram generation process. Use of this modeling technique, herein called Incremental Pay Thickness (IPT) modeling, has provided valuable insights concerning the seismic response of several offshore Gulf of Mexico amplitude anomalies. Through integration of the petrophysical data, comparisons between seismic waveform response and expected reservoir pay thickness are extended to include estimates of gross pay thickness, net pay thickness, net porosity feet of pay, and hydrocarbons in place. These 1-D synthetic data easily convert to 2-D displays that often show exceptional waveform correlations between the synthetic and actual seismic data. Anomalous observed waveform responses include complex tuning curves; diagnostic isochron measurements even in unresolved thin-bed reservoirs; and extreme variations in the seismic expression of hydro-carbon-fluid contacts. While IPT modeling examples illustrate both the variability and nonuniqueness of seismic responses to hydrocarbon reservoirs, they often show good seismic predictability of pay thickness if the appropriate choice of amplitude-isochron versus pay thickness is made (i.e., peak amplitude, trough amplitude, or average amplitude versus gross pay thickness, net pay thickness, net porosity feet of pay, or hydrocarbons in place).
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Alabeed, Adel, Zeyad Ibrahim, and Emhemed Alfandi. "DETERMINATION CONVENTIONAL ROCK PROPERTIES FROM LOG DATA & CORE DATA FOR UPPER NUBIAN SANDSTONE FORMATION OF ABU ATTIFEL FIELD." Scientific Journal of Applied Sciences of Sabratha University 2, no. 1 (April 25, 2019): 29–37. http://dx.doi.org/10.47891/sabujas.v2i1.29-37.
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A reservoir is a subsurface rock that has effective porosity and permeability which usually contains commercially exploitable quantity of hydrocarbon. Reservoir characterization is undertaken to determine its capability to both store and transmit fluid. Petrophysical well log and core data, in this paper, were integrated in an analysis of the reservoir characteristics by selecting of three productive wells. The selected wells are located at Abu Attifel field in Libya for Upper Nubian Sandstone formation at depth varied form 12921 to14330 ft. The main aim of this study is to compare the laboratory measurement of core data with that obtained from well log data in order to determine reservoir properties such as shale volume, porosity (Φ), permeability (K), fluid saturation, net pay thickness. The plots of porosity logs and core porosity versus depth for the three wells revealed significant similarity in the porosity values. The average volume of shale for the reservoir was determined to be 22.5%, and average permeability values of the three wells are above 150 md, while porosity values ranged from 9 to 11%. Low water saturation 13 to 22% in the three wells indicates the wettability of the reservoir is water-wet.
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Neff, Dennis B. "Estimated pay mapping using three‐dimensional seismic data and incremental pay thickness modeling." GEOPHYSICS 55, no. 5 (May 1990): 567–75. http://dx.doi.org/10.1190/1.1442868.
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Better estimates of hydrocarbon pay thickness and reservoir distribution are achieved if forward modeling is combined with crossplot cluster analysis before the seismic amplitude and isochron data are converted into estimates of pay thickness. To facilitate this process, an enhanced convolutional modeling technique that incorporates petrophysical data and equations into the synthetic seismogram generation process was developed. These incremental pay thickness (IPT) forward models provide the pertinent seismic and petrophysical values required for crossplot analysis. The crossplot analyses then define which seismic variables (trough amplitude, peak amplitude, time structure, isochron, etc.) are most uniquely related to a pay thickness parameter (gross thickness, net thickness, net porosity thickness, or hydrocarbons in place). Work to date, mostly in offshore Gulf Coast gas sands, has shown significant variation in the crossplot transforms required to convert seismic data to estimated pay maps. As such, an interactive, model‐based, interpretive approach is recommended as an appropriate means to integrate petrophysical, geologic, and 3-D seismic data in the creation of reservoir pay maps.
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Li, Yandong, Xiaodong Zheng, and Yan Zhang. "High-frequency anomalies in carbonate reservoir characterization using spectral decomposition." GEOPHYSICS 76, no. 3 (May 2011): V47—V57. http://dx.doi.org/10.1190/1.3554383.
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Low-frequency shadows have often been used as hydrocarbon indicators in the application of spectral decomposition. The reason behind the low-frequency anomaly has been explained as high-frequency energy attenuation caused by hydrocarbons. However, in our practice on carbonate reservoir characterization in two areas, Precaspian Basin and Central Tarim Basin, China, we encountered high-frequency anomalies, i.e., the isofrequency slices or sections at high frequencies exhibit anomalies associated with the good carbonate reservoir, particularly in the tight limestone background. We used the product of porosity and thickness as a parameter to measure the quality of the carbonate reservoir of each well and classified the 46 wells in our two studied areas into three types. Type I wells contain high-porosity thick reservoirs, type II wells contain reservoirs with moderate porosity and thickness, and type III wells contain only low-porosity thin reservoirs. The results were that 12 out of 13 type I wells exhibit high-frequency anomalies, and 30 out of 33 type II and type III wells do not exhibit high-frequency anomalies. We further validated the existence of this high-frequency anomaly by forward modeling analysis and fluid substitution experiments using the actual well-log curves measured in the carbonate reservoir. The results showed that in our two studied areas the high-frequency anomalies are more common than low-frequency shadows that can be observed only when the thickness of the reservoir is more than half of the wavelength or the reservoir rocks are extremely unconsolidated. Therefore, this high-frequency anomaly may be used as a more reliable indicator for a good carbonate reservoir than low-frequency shadows in real applications.
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Yar, Mustafa, Syed Waqas Haider, Ghulam Nabi, Muhammad Tufail, and Sajid Rahman. "Reservoir Characterization of Sand Intervals of Lower Goru Formation Using Petrophysical Studies; A Case Study of Zaur-03 Well, Badin Block, Pakistan." International Journal of Economic and Environmental Geology 10, no. 3 (November 14, 2019): 118–24. http://dx.doi.org/10.46660/ijeeg.vol10.iss3.2019.320.
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Present study deals with petrophysical interpretation of Zaur-03 well for reservoir characterization of sandintervals of Lower Goru Formation in Badin Block, Southern Indus Basin, Pakistan. Early Cretaceous Lower GoruFormation is the distinct reservoir that is producing hydrocarbons for two decades. Complete suite of wireline logsincluding GR log, Caliper log, SP log, Resistivity logs (MSFL, LLS, LLD), Neutron log and Density log along withwell tops and complete drilling parameters were analyzed in this study. The prime objective of this study was to markzones of interest that could act as reservoir and to evaluate reservoir properties including shale volume (Vsh), porosity(ϕ), water saturation (Sw), hydrocarbon saturation (Sh) and net pay thickness. Based on Petrophysical evaluation threezones have been marked in Lower Goru Formation, A Sand (1890m to 1930m), B-sand (1935m to 2010) and C-sand(2015m to 2100m). The average calculated parameters for evaluation of reservoir properties of Zaur-03 well depicts anaverage porosity of 8.92% and effective porosity of 4.81%. Water Saturation is calculated as 28.54% and HydrocarbonsSaturation is 71.46%. Analysis shows that Sh in Zaur-03 well is high so the production of hydrocarbons iseconomically feasible.
Dissertations / Theses on the topic "Net reservoir porosity thickness product"
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Jaradat, Rasheed Abdelkareem. "Prediction of reservoir properties of the N-sand, vermilion block 50, Gulf of Mexico, from multivariate seismic attributes." Diss., Texas A&M University, 2003. http://hdl.handle.net/1969.1/2236.
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The quantitative estimation of reservoir properties directly from seismic data is a major goal of reservoir characterization. Integrated reservoir characterization makes use of different varieties of well and seismic data to construct detailed spatial estimates of petrophysical and fluid reservoir properties. The advantage of data integration is the generation of consistent and accurate reservoir models that can be used for reservoir optimization, management and development. This is particularly valuable in mature field settings where hydrocarbons are known to exist but their exact location, pay, lateral variations and other properties are poorly defined. Recent approaches of reservoir characterization make use of individual seismic attributes to estimate inter-well reservoir properties. However, these attributes share a considerable amount of information among them and can lead to spurious correlations. An alternative approach is to evaluate reservoir properties using multiple seismic attributes. This study reports the results of an investigation of the use of multivariate seismic attributes to predict lateral reservoir properties of gross thickness, net thickness, gross effective porosity, net-to-gross ratio and net reservoir porosity thickness product. This approach uses principal component analysis and principal factor analysis to transform eighteen relatively correlated original seismic attributes into a set of mutually orthogonal or independent PC??s and PF??s which are designated as multivariate seismic attributes. Data from the N-sand interval of Vermilion Block 50 field, Gulf of Mexico, was used in this study. Multivariate analyses produced eighteen PC??s and three PF??s grid maps. A collocated cokriging geostaistical technique was used to estimate the spatial distribution of reservoir properties of eighteen wells penetrating the N-sand interval. Reservoir property maps generated by using multivariate seismic attributes yield highly accurate predictions of reservoir properties when compared to predictions produced with original individual seismic attributes. To the contrary of the original seismic attribute results, predicted reservoir properties of the multivariate seismic attributes honor the lateral geological heterogeneities imbedded within seismic data and strongly maintain the proposed geological model of the N-sand interval. Results suggest that multivariate seismic attribute technique can be used to predict various reservoir properties and can be applied to a wide variety of geological and geophysical settings.
Book chapters on the topic "Net reservoir porosity thickness product"
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"Main Characteristics of an Aquifer The main function of the aquifer is to provide underground storage for the retention and release of gravitational water. Aquifers can be characterized by indices that reflect their ability to recover moisture held in pores in the earth (only the large pores give up their water easily). These indices are related to the volume of exploitable water. Other aquifer characteristics include: • Effective porosity corresponds to the ratio of the volume of “gravitational” water at saturation, which is released under the effect of gravity, to the total volume of the medium containing this water. It generally varies between 0.1% and 30%. Effective porosity is a parameter determined in the laboratory or in the field. • Storage coefficient is the ratio of the water volume released or stored, per unit of area of the aquifer, to the corresponding variations in hydraulic head 'h. The storage coefficient is used to characterize the volume of useable water more precisely, and governs the storage of gravitational water in the reservoir voids. This coefficient is extremely low for confined groundwater; in fact, it represents the degree of the water compression. • Hydraulic conductivity at saturation relates to Darcy’s law and characterizes the effect of resistance to flow due to friction forces. These forces are a function of the characteristics of the soil matrix, and of the fluid viscosity. It is determined in the laboratory or directly in the field by a pumping test. • Transmissivity is the discharge of water that flows from an aquifer per unit width under the effect of a unit of hydraulic gradient. It is equal to the product of the saturation hydraulic conductivity and of the thickness (height) of the groundwater. • Diffusivity characterizes the speed of the aquifer response to a disturbance: (variations in the water level of a river or the groundwater, pumping). It is expressed by the ratio between the transmissivity and the storage coefficient. Effective and Fictitious Flow Velocity: Groundwater Discharge As we saw earlier in this chapter, water flow through permeable layers in saturated zones is governed by Darcy’s Law. The flow velocity is in reality the fictitious velocity of the water flowing through the total flow section. Bearing in mind that a section is not necessarily representative of the entire soil mass, Figure 7.7 illustrates how flow does not follow a straight path through a section; in fact, the water flows much more rapidly through the available pathways (the tortuosity effect). The groundwater discharge Q is the volume of water per unit of time that flows through a cross-section of aquifer under the effect of a given hydraulic gradient. The discharge of a groundwater aquifer through a specified soil section can be expressed by the equation:." In Hydrology, 229–30. CRC Press, 2010. http://dx.doi.org/10.1201/b10426-57.
Full textConference papers on the topic "Net reservoir porosity thickness product"
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Mabrouk, Ibrahim. "Integrating XRD and Well Logging Data to Establish Electro-Facies and Permeability Models for an Unconventional Heterogeneous Tight Gas Reservoir, Obaiyed Giant Gas Field." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/208626-stu.
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Abstract Formation evaluation in heterogeneous reservoirs can be very challenging especially in fields that extend over several kilometers in area where the permeability varies from 0.1 mD up to 1000 D within the same porosity. The porosity, hydrocarbon saturation and net sand thickness in most of Obaiyed field wells are consistent; hence, the productivity of these wells is enormously dependent on the reservoir permeability. Since the permeability is highly heterogeneous, initial production rate of the wells varies between few MMSCFD to almost one hundred MMSCFD. The huge permeability variation led to a tremendous uncertainty in the dynamic modeling, which resulted in an inaccurate production forecast affecting the field economics estimation. Understanding permeability distribution and heterogeneity in Obaiyed field is the key factor for establishing a realistic permeability model, which will lead to a successful field development strategy. Extensive work was performed to understand key factors that govern the permeability in Obaiyed using the data of 1-kilometer length of cores acquired in more than 50 wells covering different reservoir properties in the field. Core data were used to separate the reservoir into different Hydraulic Flow Units (HFU) according to Amaefule's work performed on the Kozeny-Carmen model. Afterwards, a correlation between the HFU and well logs was established using IPSOM Electro-Facies module in order to define the flow units in un-cored wells. The result of this correlation was used to calibrate a Porosity-Permeability relationship for each flow unit. The next step was examining the clay-type distribution and diagenesis in each flow unit using the petrographic analysis (XRD) results from the core xdata. All factors controlling the permeability can now be represented in hydraulic flow units which are considered as a method of measurement of the reservoir quality. Consequently, property maps were constructed showing the location and continuity of each of the flow units, leading to a more deterministic approach in the well placement process. Based on this new work methodology, a production cut-off criteria relating the reservoir productivity to both clay minerals presence and percentages was established for multiple wells scenarios. As a result, the development strategy of the field changed from only vertical wells to include horizontal wells as well which proved to be the only economic approach to produce the Illite dominated zones. This paper presents a workflow to provide a representative estimation of permeability in extremely heterogeneous reservoirs especially the ones dominated by complex clay distribution.
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Elmohammady, Raed Mohamed, Mostafa Mahrous Ali, and Hassan Elsayed Salem. "Successful Unlock for Non-Continuous Sand of Tight Gas Reservoir using Horizontal Wells." In SPE/IADC Middle East Drilling Technology Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/202120-ms.
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Abstract Reservoir development in Safa Formation requires a lot of vertical wells in order to exploit the gas reserve in the formation which means high cost is needed because the heterogeneity in the formation is noticed due to sandstone is pinched out in different locations of the reservoir. So, vertical well may be sweep from limited area of the reservoir that make safa formation has less priority for new activities. Form all of that the plan was drilling horizontal wells with long horizontal section to recover great volume of gas from reservoir. In addition to reduction in number of drilling vertical wells in the reservoir. In contrast, the major constrains is the small thickness of reservoir that make drilling horizontal section is very difficult. The main characteristics of safa formation is non continuous sandstone in the whole reservoir with great heterogeneity that not controlled by any points in the reservoir for the distribution of sandstone. In addition, there are a lot of locations in safa formation that include lean intervals which have kaolinite, elite that are not capable for produce from sand. In other hand, there is another constrains beside the discontinuity of sand production is the heterogeneity of permeability properties of reservoir that change in wide range across the reservoir with minimum range of 0.01 md and increase in some locations to reach 100 md. From all of the previous, it is a big challenge in drilling horizontal wells with long horizontal section in thin reservoir thickness in order to access the best reservoir permeability and optimize the number of drilling wells based on this concept. This paper will discuss case study of unlock and development long horizontal section in gas reservoir characterized by its tightness. The main goal of this horizontal well to recover ultimate gas reserve from safa formation by horizontal section reached to 2000 meter with a challenge because it is abnormal to drill this large horizontal section in western desert of Egypt in reservoir thickness range from 5 meter to 30 meter as prognosis from other offset wells in case of there is no pitchout of the sandstone. After Drilling of first horizontal well, the results were unexpected because the well penetrates a large horizontal section of sandstone in safa formation. This section reached to around 1750 meter with average reservoir permeability between 10 – 20 md and the reservoir porosity about 13% with good hydrocarbon saturation that changes along this section from 75% to 80%. So, this well put on production with very stable gas production rate 20 MMSCFD. In this paper will discuss in details the different challenge that faced to unlock this tight gas reservoir and will discuss the performance of horizontal well production. In this paper will discuss the first horizontal well in safa formation and the longest horizontal section in western desert of Egypt in tight gas formation that has a lot of challenges and risks are faced. After success the concept of horizontal well in heterogeneous reservoir, the next plan is the development of this reservoir using several horizontal wells to recover the ultimate recovery of gas from safa formation.
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Kasap, Ekrem, and James Wang. "An Integrated Study for a Condensate Reservoir to Optimize Gas Production." In ASME 2001 Engineering Technology Conference on Energy. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/etce2001-17107.
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Abstract Q2-Sand of MC486, Gulf Coast is a mature low yield, condensate reservoir. The two issues to be resolved were 1) in-fill drilling requirements to optimize the production against early watering out of the existing wells, and 2) compressor schedules and capacities once the pressure is lower than the platform requirements. A new numerical flow model based on a geological, log, seismic, and production data was needed to resolve the issues. A multi-disciplinary characterization study to formulate final re-development and production optimization schemes is undertaken. The static reservoir model was built from the 3-D seismic interpretations for the upper and the lower horizons. Thickness variations across the field and by horizons were estimated from thickness-amplitude correlations. Saturation, porosity, and net-to-gross ratio values were obtained from the core and log data. Variable directional permeabilities were calculated by a flow based upscaling technique using net-to-gross ratios and clean-sand and shale permeabilities. The compositional characteristics of the production were simulated with a fully compositional flow model. The G&G model delineated Northern Prospect and the Main Reservoir. Both of these features were included into the numerical flow model along with the partially active aquifer that separates them. The numerical model was initialized and calibrated to the historical production data at the six wells. The current average pressure of the Northern Prospect is obtained. An additional aquifer support for the upper and lower sands was resolved, and the cross-flow spots between them were identified. The integrated study was critical for optimizing recovery from this field. The optimum development plan recommends adding compressors and making re-completions to the upper sand and anticipates the recovery of 37 BCF more gas than previously predicted. Upper sand re-completions would drastically reduce water production and its handling costs as verified by a very recent re-completion job at an existing well.
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Wijaya, Aditya Arie, Ivan Zhia Ming Wu, Sarvagya Parashar, Mohammad Iffwad, Amirul Afiq B. Yaakob, William Amelio Tolioe, Adib Akmal Che Sidid, and Nadhirah Bt. Ahmad. "INTEGRATED EVALUATION OF LAMINATED SAND-SHALE GAS-BEARING RESERVOIR USING TENSOR MODEL: A CASE STUDY COMBINING DATA FROM TRIAXIAL RESISTIVITY, IMAGE, SONIC, AND RESERVOIR TESTING IN B-FIELD, MALAYSIA." In 2021 SPWLA 62nd Annual Logging Symposium Online. Society of Petrophysicists and Well Log Analysts, 2021. http://dx.doi.org/10.30632/spwla-2021-0043.
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In recent years, the development of frontier areas brings added challenges to formation evaluation, especially thinly bedded reservoirs. It is challenging to evaluate such reservoirs due to the low resistivity values and high shale volume, which masks the contrast between water and hydrocarbon zones. Using conventional approaches in these types of reservoirs will underestimate the hydrocarbon potential and reserves estimates. A study has been carried out of the thin-bed laminated reservoir in B-field using the tensor model technique to assess the hydrocarbon potential. Additional data from borehole imaging and sonic logs are critical for enhancing the evaluation of hydrocarbon potential and complements the result of the tensor model evaluation. The study was conducted to calculate the sand resistivity and sand porosity using a combination of the tensor model and the Thomas-Stieber model. The tensor model uses acquired horizontal and vertical resistivities, while the Thomas-Stieber model uses the calculated shale volume and porosity. One of the main parameters in the tensor model is shale resistivity, which upon analysis, varies across many shale sections in the well. This uncertainty is reduced by picking multiple shale resistivity values based on borehole image facies analysis. The VPVS ratio technique and Brie’s plot using compressional and shear travel time are used as a qualitative analysis that indicates the same gas-bearing interval. The tensor model calculations improve hydrocarbon saturation by a range of 4-21%, depending on sand thickness and shale volume, which increases the net to gross by more than 20%. The borehole image facies analysis helps to objectively pick the shale resistivity parameters to avoid subjective interpretation and underestimating the pay. A qualitative approach using sonic data helps to identify the potential gas-bearing interval and complement the previous tensor model interpretation. Although all interpretation methods indicate a similar gas-bearing interval that correlates with the mudlog total gas reading, the combination of the tensor and Thomas-Stieber method with image constrained shale resistivities gives the most definitive gas saturation and net pay The novelty of this study is to showcase two things. First is the application of combined tensor and Thomas-Stieber model in a laminated reservoir, with image constrained shale resistivity for improved gas saturation and net pay. The second is to highlight the use of gas-sensitive sonic data to confirm the gas saturated interval.
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Booncharoen, Pichita, Thananya Rinsiri, Pakawat Paiboon, Supaporn Karnbanjob, Sonchawan Ackagosol, Prateep Chaiwan, and Ouraiwan Sapsomboon. "Pore Pressure Estimation by Using Machine Learning Model." In International Petroleum Technology Conference. IPTC, 2021. http://dx.doi.org/10.2523/iptc-21490-ms.
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Abstract In the past few years, over hundreds of wells were drilled in Gulf of Thailand, had faced with the depletion and lost circulation issues resulted from a lack of pressure data. A prior research of reservoir depletion pressure (Fangming, 2009) in oil field, China was obtained from multivariate statistic and regression by using density and neutron porosity log curves in logging-while-drilling data. However, the relative errors are 7.5% from the actual formation pressure. Thus, there are several latent variables in the model like drilling parameters (Rehm, 1971) which part of formation pressure. From 2018 initiative model in Satun-Funan, the classification model was obtained by using mud gas, porosity, water saturation, net sand thickness, net-hydrocarbon-pore thickness and neutron-density separation. However, the limitation is drilling parameters could not account by classifier, and accurate only original pressure category. So, this study has expanded scope to include other reservoir properties and drilling parameters then applied with machine learning on offset well dataset by using three regressors such quantile, ridge and XGBoost regressors. The pore pressure estimation model aims to improve efficiency for making decision in execution phase, increasing confidence in perforation strategy. The model parameters, pay thickness, porosity, water saturation, original pressure from local pressure profile and total gas show are accounted into this model. As of regressor assumption, some facts are conducted to logarithm and perform 2nd polynomial feature for model flexibility. There are three steps for building model such as data manipulation, analysis and deployment. Two purposes of pressure prediction impact algorithm selection, for operational phase, quantile regressor is implemented to provide conservative prediction while Ridge or XGBoost regressors are alternatives for perforation strategy, provide mid case result of pressure prediction. Overall model performance was measured using root mean square error (RMSE) on train & test dataset which show approximately 1.2 and 1.5 ppg range of accuracy respectively from total 12 drilling projects in Pattani basin. Overall model fitting is within reasonable range of generalization capacity to apply with unknown data point (test set). The future model will continue to improve accuracy and manage imbalanced dataset between original pressure and depleted sands.
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Moussa, Tamer, Hassan Dehghanpour, and Melanie Popp. "Reservoir Quality Versus Completion Intensity: An Application of Supervised Fuzzy Clustering on Western Canadian Well Data." In SPE Hydraulic Fracturing Technology Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/204194-ms.
Full textAbstract:
ABSTRACT The industry is facing significant challenges due to the recent downturn in oil prices, particularly for the development of tight reservoirs. It is more critical than ever to 1) identify the sweet spots with less uncertainty and 2) optimize the completion-design parameters. The overall objective of this study is to quantify and compare the effects of reservoir quality and completion intensity on well productivity. We developed a supervised fuzzy clustering (SFC) algorithm to rank reservoir quality and completion intensity, and analyze their relative impacts on wells' productivity. We collected reservoir properties and completion-design parameters of 1,784 horizontal oil and gas wells completed in the Western Canadian Sedimentary Basin. Then, we used SFC to classify 1) reservoir quality represented by porosity, hydrocarbon saturation, net pay thickness and initial reservoir pressure; and 2) completion-design intensity represented by proppant concentration, number of stages and injected water volume per stage. Finally, we investigated the relative impacts of reservoir quality and completion intensity on wells' productivity in terms of first year cumulative barrel of oil equivalent (BOE). The results show that in low-quality reservoirs, wells' productivity follows reservoir quality. However, in high-quality reservoirs, the role of completion-design becomes significant, and the productivity can be deterred by inefficient completion design. The results suggest that in low-quality reservoirs, the productivity can be enhanced with less intense completion design, while in high-quality reservoirs, a more intense completion significantly enhances the productivity. Keywords Reservoir quality; completion intensity; supervised fuzzy clustering, approximate reasoning,tight reservoirs development
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Schrynemeeckers, Rick. "Acquire Ocean Bottom Seismic Data and Time-Lapse Geochemistry Data Simultaneously to Identify Compartmentalization and Map Hydrocarbon Movement." In Offshore Technology Conference. OTC, 2021. http://dx.doi.org/10.4043/30975-ms.
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Abstract Current offshore hydrocarbon detection methods employ vessels to collect cores along transects over structures defined by seismic imaging which are then analyzed by standard geochemical methods. Due to the cost of core collection, the sample density over these structures is often insufficient to map hydrocarbon accumulation boundaries. Traditional offshore geochemical methods cannot define reservoir sweet spots (i.e. areas of enhanced porosity, pressure, or net pay thickness) or measure light oil or gas condensate in the C7 – C15 carbon range. Thus, conventional geochemical methods are limited in their ability to help optimize offshore field development production. The capability to attach ultrasensitive geochemical modules to Ocean Bottom Seismic (OBS) nodes provides a new capability to the industry which allows these modules to be deployed in very dense grid patterns that provide extensive coverage both on structure and off structure. Thus, both high resolution seismic data and high-resolution hydrocarbon data can be captured simultaneously. Field trials were performed in offshore Ghana. The trial was not intended to duplicate normal field operations, but rather provide a pilot study to assess the viability of passive hydrocarbon modules to function properly in real world conditions in deep waters at elevated pressures. Water depth for the pilot survey ranged from 1500 – 1700 meters. Positive thermogenic signatures were detected in the Gabon samples. A baseline (i.e. non-thermogenic) signature was also detected. The results indicated the positive signatures were thermogenic and could easily be differentiated from baseline or non-thermogenic signatures. The ability to deploy geochemical modules with OBS nodes for reoccurring surveys in repetitive locations provides the ability to map the movement of hydrocarbons over time as well as discern depletion affects (i.e. time lapse geochemistry). The combined technologies will also be able to: Identify compartmentalization, maximize production and profitability by mapping reservoir sweet spots (i.e. areas of higher porosity, pressure, & hydrocarbon richness), rank prospects, reduce risk by identifying poor prospectivity areas, accurately map hydrocarbon charge in pre-salt sequences, augment seismic data in highly thrusted and faulted areas.
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Syahputra, A. "Oil Saturation Log Prediction Using Neural Network in New Steamflood Area." In Digital Technical Conference. Indonesian Petroleum Association, 2020. http://dx.doi.org/10.29118/ipa20-g-307.
Full textAbstract:
Surveillance is very important in managing a steamflood project. On the current surveillance plan, Temperature and steam ID logs are acquired on observation wells at least every year while CO log (oil saturation log or SO log) every 3 years. Based on those surveillance logs, a dynamic full field reservoir model is updated quarterly. Typically, a high depletion rate happens in a new steamflood area as a function of drainage activities and steamflood injection. Due to different acquisition time, there is a possibility of misalignment or information gaps between remaining oil maps (ie: net pay, average oil saturation or hydrocarbon pore thickness map) with steam chest map, for example a case of high remaining oil on high steam saturation interval. The methodology that is used to predict oil saturation log is neural network. In this neural network method, open hole observation wells logs (static reservoir log) such as vshale, porosity, water saturation effective, and pay non pay interval), dynamic reservoir logs as temperature, steam saturation, oil saturation, and acquisition time are used as input. A study case of a new steamflood area with 16 patterns of single reservoir target used 6 active observation wells and 15 complete logs sets (temperature, steam ID, and CO log), 19 incomplete logs sets (only temperature and steam ID) since 2014 to 2019. Those data were divided as follows ~80% of completed log set data for neural network training model and ~20% of completed log set data for testing the model. As the result of neural model testing, R2 is score 0.86 with RMS 5% oil saturation. In this testing step, oil saturation log prediction is compared to actual data. Only minor data that shows different oil saturation value and overall shape of oil saturation logs are match. This neural network model is then used for oil saturation log prediction in 19 incomplete log set. The oil saturation log prediction method can fill the gap of data to better describe the depletion process in a new steamflood area. This method also helps to align steam map and remaining oil to support reservoir management in a steamflood project.