Stock Tank Oil Initially In Place Research Articles

Analysis of Reservoir Properties and Quantification of Hydrocarbon Volumes Within LK Field, Niger Delta, Nigeria

This work analyzes and estimates the qualities and volumes of hydrocarbons in the identified reservoirs (Thin Sand and Sand B) of the LK field in the Niger Delta, Nigeria. The LK field is a promising hydrocarbon reservoir located at the border of the Greater Ughelli Depobelt in the Niger Delta Basin. The data utilized encompassed a 3D seismic survey, which was analyzed to delineate faults, identify stratigraphic horizons, and generate maps illustrating the time and depth structures within the subsurface. Well log data, including gamma ray, resistivity, and density/neutron measurements, were analyzed to evaluate and describe the petrophysical characteristics of the subsurface rock formations. The Thin Sand reservoir unit contains natural gas, while the Sand B reservoir is divided into two separate zones: the first zone (Z1) contains natural gas, and the second zone (Z2) contains oil. For Sand B, Z1, and Z2, the gross thicknesses are 13.16m and 57.46m, net thicknesses are 11.32m and 45.39m, NTGs are 0.86 and 0.79, shale volumes (Vsh) are 0.13 and 0.21, effective porosities (?e) are 0.28 and 0.21, water saturations (Sw) are 0.11 and 0.39, and hydrocarbon saturations (Sh) are 0.89 and 0.61, respectively. For the Thin Sand reservoir, the gross thickness is 6.00m, net thickness is 4.74m, NTG is 0.79, Vsh is 0.21, ?e is 0.23, Sw is 0.12, and Sh is 0.88. The stock tank oil initially in place (STOIIP) in the Sand B, Z2 reservoir is estimated to be 46.8 million barrels, with a recoverable oil volume of 9.4 million barrels, assuming a 20% recovery factor. The stock tank gas initially in place (STGIIP) is estimated at 10.4 billion cubic feet (Bcf) in the Thin Sand reservoir and 30.6 Bcf in the Sand B, Z1 reservoir, with recoverable gas volumes projected at 8.3 Bcf and 24.5 Bcf, respectively, assuming 80% recovery factors. After estimating the volume of hydrocarbons in the known reservoirs, significant and economic amounts of gas and oil for commercial purposes were discovered. However, this research study faces challenges such as uncertainty, unreliability, and varying scales due to different origins within the field. Further research using unconventional computational tools together with high-resolution simulating software is needed to produce more detailed and accurate results.

Integration of Seismic and Well Log Data for Reservoir Characterization in Offshore Niger Delta, Nigeria

The demand for fossil fuels is continually increasing due to the growing global population and industrialization. It is thus necessary to find hydrocarbon prospects in new fields and those that have previously been classified as marginal fields in order to maximize production. An integrated approach is required to effectively characterize hydrocarbon reservoirs and assess their ability to store and produce hydrocarbons. 3D seismic reflection data and well log data were combined to quantitatively estimate hydrocarbon reserves in a field, offshore Niger delta, Nigeria. The reservoirs were delineated on the gamma ray and resistivity logs which penetrate four wells selected from the field. The petrophysical analysis provided information about the net-to-gross thickness ratio, porosity, shale volume and water saturation of the reservoirs, deduced from well log suites comprising gamma, resistivity, density and neutron-porosity logs through four wells. The seismic interpretation involved mapping of horizons and faults across the wells on the seismic section. Check shot data were used to tie the seismic data to the well log data to generate the synthetic seismogram. The time structural and depth structural maps were generated. The volumetric analysis entailed derivation of the Gross rock volume from the depth structural map, and estimation of the Stock Tank Oil Initially In Place (STOIIP). Four reservoirs were delineated in each of the four wells. The average thickness of the reservoirs ranges from 56.6 m to 232.7 m while the water saturation varies from 0.29% to 0.57%. The average porosities of the reservoirs ranges from 0.18% to 0.22%. The structural interpretation of the eight faults mapped reveals synthetic and antithetic faults, and rollover anticlines. The time- and depth structural maps generated from the mapped horizons show that the reservoirs are penetrated by the different faults. The Stock Tank Oil Initially In Place (STOIIP) of the reservoirs range from 25 MMstb to 468 MMstb. The study shows that the integration of 3D reflection data and well log data can be used effectively to estimate hydrocarbon reserves. The results of the study are expected to contribute to the development of new exploration and production strategies in the Niger delta basin and similar sedimentary environments.

Study Reviews Largest ASP Project From Laboratory to Pilots and Field Application

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 215058, “A Systematic Review of the Largest ASP Flood Project in the World: From Laboratory to Pilots and Field Application,” by Yunan Wei, SPE, Xiaoguang Lu, SPE, and Jianhong Xu, SPE, C&C Reservoirs, et al. The paper has not been peer reviewed. _ The complete paper presents a systematic review of the largest alkaline-surfactant-polymer (ASP) flood project in the world, applied in the largest oil field in China. First, reservoir and fluid characteristics are highlighted to understand heterogeneity of the reservoir. Next, project history is summarized, including laboratory studies, pilot tests, industrial-scale tests, and fieldwide application. Finally, typical ASP flood performance and reservoir management measures from over 30 years of experience are presented. Performances of ASP flood and polymer floods in the same field also are compared.​​​​ Introduction In the La-Sa-Xing Field, ASP flooding was studied in the laboratory from 1987 to 1993 and followed by five small-scale pilots from 1994 to 1999, all successfully achieving incremental recoveries of approximately 20% stock-tank oil initially in place (STOIIP). As a result, industrial-scale pilots were conducted from 2000 to 2007, resulting in increased production by ASP flooding from 3,887 to greater than 19,000 BOPD in 2007. Fieldwide ASP expansion was launched in December 2007. By 2021, the ASP-flooded blocks registered a STOIIP of 1.9823 billion bbl. Daily production was approximately 96,000 BOPD through approximately 9,650 wells. Average incremental recovery factor was 20% STOIIP with waterflooding and 8% with polymer flooding, providing an ultimate recovery factor of 60%. Cumulative oil production by ASP flooding had reached 316 million bbl by 2021, making it the largest ASP flooding project in the world. Geological Background and Reservoir Characteristics The La-Sa-Xing Field is in the north of the Songliao Basin of northeast China, comprising the majority of the Daqing field complex. The field was placed onstream in 1960. The hydrocarbon-bearing reservoir has a gross thickness of 1,377 ft and a net thickness of 394 ft. Net pay averages 150 ft. Initial reservoir pressure ranges from 1,523 to 2,585 psi. Reservoir temperature varies from 113 to 122°F. Crude oil has an API gravity of 33°, a viscosity of 8.5–10.3 cp at reservoir conditions, an initial gas/oil ratio of 258 scf/STB, and a bubblepoint pressure of 1,291 psi. Formation water salinity is 7000 mg/L. Reservoir rock initially shows water or weak oil wettability. Depending on permeability, three types of reservoir sand (Type I, Type II, and Type III) have been identified. Currently, ASP flooding is mainly applied to Type I sand, with partial application to Type II Sand.

Efforts Lead to Formulation of High-Performance ASP

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper IPTC 22729, “ASP Formulation Development Journey: Optimization, Validation, and Quality Control for Mangala Field,” by Nitish Koduru, Dhruva Prasad, SPE, and Amitabh Pandey, SPE, Cairn Oil and Gas. The paper has not been peer reviewed. Copyright 2023 International Petroleum Technology Conference. Reproduced by permission. _ Mangala is a large low-salinity, high-quality fluvial oil field in India with stock-tank oil initially in place (STOIIP) of more than 1 billion bbl of waxy and moderately viscous crude. Aqueous-based chemical enhanced oil recovery (EOR) has been identified as the most suitable technique to improve recovery over waterflooding. The objective of the complete paper is to describe alkaline/surfactant/polymer (ASP) formulation development for Mangala, which involved more than 30 corefloods at the time of writing, with formulation design changing over time. Field Background The Mangala field has been regarded as an excellent chemical EOR candidate since its discovery in 2004. The main reservoir unit is divided into the Lower and Upper Fatehgarh formations. These units are subdivided into five reservoir units, FM1 to FM5 from top to bottom. Mangala contains waxy sweet crude oil with gravity ranging from 20 °API near the oil/water contact to 28 °API in the oil column. The crude has in-situ viscosity of 9–17 cp. The crude has good napthenic acid content and reacts with alkali to produce in-situ soap. Immediately after the field’s appraisal stage, work to identify the most suitable EOR process began. First, a polymerflooding pilot was conducted during 2011–12. The encouraging results led to full-field polymerflooding implementation in November 2014. The ASP pilot performed well; incremental oil recovery over polymerflooding was estimated to be in the range of 20–25% of the pilot STOIIP. The initial development plan involved implementing a hot waterflooding production startup to maintain reservoir pressure and effective sweep. The Upper Fatehgarh FM1 and FM2 units were developed with inverted nine-spot patterns, while the more-homogeneous lower Fatehgarh (FM3 and FM4) were developed with downdip injectors and updip horizontal producers. The Mangala field began producing under a hot waterflood in 2009, with the injected water heated to approximately 80–85°C to avoid wax deposition. Injection was started within a few months of first production. At the time of writing, the field is under polymerflooding, with results largely in line with expectations. The field, which has already produced approximately 37% of the STOIIP, is on a declining production trend, and large-scale ASP flooding is being considered as the next development initiative to arrest production decline and increase overall recovery. The complete paper discusses EOR screening studies; ASP formulations, including the initial formulation; the method adopted for selection of chemical suppliers for the pilot test; optimization of ASP formulations tested in the pilot; validation of the developed formulation to other layers of the field; and planned quality-control processes to be used during procurement of chemicals for larger applications of ASP floods in the field. This synopsis concentrates on the last three of these factors, rather than the formulations considered, which, in addition to the initial formulation, included the following: - Formula 2: ASP formulation with a sacrificial surfactant - Formula 3: ASP formulation with a single surfactant - Formula 4: Formulation with a highly hydrophilic, large-hydrophobe surfactant

A Systematical Review of the Largest Polymer Flood Project in the World: From Laboratory to Pilots and Field Application

Summary This paper presents a systematical review of the largest polymer flood project in the world, applied to multilayered, heterogeneous sandstone reservoirs in the giant Daqing Oilfield in China. First, reservoir and fluid characteristics are highlighted to understand the heterogeneity of the reservoir. Next, the project history is summarized, including laboratory studies, pilot tests, commercial tests, and fieldwide applications. Third, typical polymer flood performance and reservoir management measures are presented. Finally, key understandings and lessons learned from more than 50 years of experience are summarized. The La-Sa-Xing Field in the Daqing Field Complex contains three types of reservoir sands: Type I sand with high permeability, Type II sand with medium permeability, and Type III sand with low permeability. Polymer flood was studied in the laboratory in the mid 1960s, followed by small-scale pilots beginning in 1972 and industrial-scale pilots starting in 1993, all of which successfully reduced water cut and enhanced oil recovery. Fieldwide application commenced in 1996, targeting the Type I sand. With Type II sand being brought onstream in 2003, the project achieved a peak production of 253,000 BOPD in 2013. Polymer flood reduced water cut by 24.8%. Reservoir management measures, such as zonal injection, profile modification, hydraulic fracturing in low-permeability sand, and injection optimization, proved to be effective. Based on the water-cut performance, production can be divided into four stages: (1) water-cut decline, (2) low water cut, (3) rebound, and (4) water chase. Fit-for-purpose improved-oil-recovery measures were implemented for each stage to improve production performance. Key understandings and lessons learned include the following: (1) Polymer flood improves both sweeping and displacing efficiencies; (2) high interlayer permeability contrast leads to low incremental recovery; (3) variable well spacing should be adopted for different reservoir types; (4) adoption of large molecular weight (MW) and large slug size greatly enhances recovery; and (5) salt-resistant polymer is beneficial for produced water reinjection in Type II sand; (6) zonal injection increased swept reservoir zones by 9.8% and swept pay thickness by 10.3%; (7) profile modifications helped improve vertical conformance in injection wells and led to enhanced sweeping efficiency and extended low water-cut stage; and (8) optimization-recommended well spacing for Type I, Type II, and Type III sands is 10–15.5, 5.6–7.6, and 2.5–3.6 acres, respectively. In comparison with generally 6–8% incremental recovery by polymer flood in the industry, this project achieved an impressive incremental recovery of 12%, enhancing the oil recovery factor from 40% by primary recovery and waterflood to 52% stock tank oil initially in place (STOIIP). The progressive approach from laboratory experiments through pilots and finally to field application is a best practice for applying polymer flood fieldwide for a giant field such as the La-Sa-Xing Field.

Petroleum system analysis-conjoined 3D-static reservoir modeling in a 3-way and 4-way dip closure setting: Insights into petroleum geology of fluvio-marine deposits at BED-2 Field (Western Desert, Egypt)

Imperfect determination of petroleum system processes coincidence, entrapment and charge timing, along with reservoir heterogeneity can considerably cause high risks throughout exploration and development phases of petroleum. Therefore, a complete subsurface visualization of the petroleum system nature, elements and processes, is badly required. To this end, we corroborated, in this study, static reservoir modeling with petroleum system analysis workflows, to better characterize the Cenomanian fluvio-marine reservoir, sandstones of Bahariya Formation, at Bed-2 Field, Abu Gharadig basin (Western Desert, Egypt). We used dataset of 2D seismic profiles and well logs of eight wells. The geometry and property of the reservoir were acquired performing static reservoir geocellular modeling approach. The geohistory, timing of charge, migration pathways, and accumulation sites were identified performing 1D and 2D basin modeling approaches. Combining both approaches was aimed at identifying new petroleum prospect areas, and estimating the hydrocarbon volumes, that are the need for such poorly-defined petroleum systems area. As indicated by the constructed, robust, reservoir and 1D-2D basin models, an additional hydrocarbon prospect, to the north central part of Bed-2 Field, is proposed to be drilled during the further oilfield development phases of the area. This prospect has all features that adequately lead to reliable inferences regarding the ultimate petroleum potential of the area. • Reservoir modeling delineating geometry and property, with depositional facies analysis unlocking reservoir heterogeneity • Petroleum system analysis workflow defining the hydrocarbon charge timing, confirming the hydrocarbon potential of the area • Pixel-based stochastic simulation algorithms modeling the rock property. • Hydrocarbon volumes assessment, gas initially in place (GIIP) and stock-tank oil initially in place (STOIIP), in the area • Defining new prospect areas, justifying future oilfield development plans

Seismic Interpretation and Reservoir Static Model: A Case Study in Block MFK, Riau Province, Indonesia

MFK Block was located between Kampar and Rokan Hulu, Riau Province and 135 from Pekanbaru City, Indonesia. There are 33 wells in Field X, MFK Block with 27 active wells. This field has an area of about 79.65 km2 that located in Central Sumatra Basin. The field was discovered in 1976 and began to be produced in January 1979. Our research is focused on AK reservoir intervals, which is also part of Bekasap formation. The main aims of this study are to interpret field structure model, determine the distribution of reservoir properties, develop static reservoir model for field as a reference for field performance enhancement, estimate oil reserves in the field reservoir, and the prospect of hydrocarbons in the AK reservoir. The available data are 2D seismic data, mudlog descriptions, well log data, and perforation data. The methods used in this study are stratigraphic sequences, electrofacies analysis, geological structure analysis, static reservoir modelling, and estimation of hydrocarbon reserve volumes. Based on mudlog and electrofacies analysis, the study interval was arranged into 2 lithofacies units, namely sand channel and sand bar. The depostion environment of Bekasap Formation is estuarine environments. The interval of the study has an association of fasies moving northeast to southwest. Based on the results of property reservoir analysis, facies that have good reservoir quality is sand channel facies. Based on the static modeling method approach, the estimated stock tank oil initially in place (STOIIP) for AK reservoir interval is 728 MBBL.

Mangala Polymer Flood Performance: Connecting the Dots Through In-Situ Polymer Sampling

Summary The Mangala field contains medium-gravity viscous crude oil. Notably, it is the largest polymer flood in India and 34% of the stock tank oil initially in place (STOIIP) has been produced in 11 years. Mangala was put on full field polymer flood in 2015, 6 years after the start of field production on waterflood in 2009. Polymer flood added nearly 93 million barrels above the anticipated waterflood recovery in 6 years. Reservoir simulation models could replicate the initial Mangala polymer flood performance. However, the performance of the lower layers of Mangala (FM-3 and FM-4) continued to progressively deviate from modeling estimates. Importantly, the observed polymer breakthrough deviated significantly from predictions. As the polymer flood matured, the trend of field water cut with time indicated that in-situ polymer viscosity was equivalent to only 50 to 60% of the surface polymer viscosity. For better predictions and corrective actions, it was necessary to understand the nature of degradation, the progressively deteriorating field performance, especially of the lower layers, and the deviation of polymer breakthrough trends from predictions. Carefully designed in-situ polymer sampling, laboratory studies, and reservoir modeling studies helped connect the dots to understand the field performance. There are several excellent publications on accelerated aging studies and some on polymer sampling. This paper offers an opportunity to directly compare experimental results with field data. The procedures used and lessons learned during field sampling can be useful for other operators for management of polymer floods.

Hydrocarbon Reservoir Characterization of ‘Khume’ Field, Offshore Niger Delta, Nigeria

The integrative approach of well log correlation and seismic interpretation was adopted in this study to adequately characterize and evaluate the hydrocarbon potentials of Khume field, offshore Niger Delta, Nigeria. 3-D seismic data and well logs data from ten (10) wells were utilized to delineate the geometry of the reservoirs in Khume field, and as well as to estimate the hydrocarbon reserves. Three hydrocarbon-bearing reservoirs of interest (D-04, D-06, and E-09A) were delineated using an array of gamma-ray logs, resistivity log, and neutron/density log suites. Stratigraphic interpretation of the lithologies in Khume field showed considerable uniform gross thickness across all three sand bodies. Results of petrophysical evaluations conducted on the three reservoirs correlated across the field showed that; shale volume ranged from 7-14%, total and effective porosity ranged from 19-26% and 17-23% respectively, NTG from 42 to 100%, water saturation from 40%-100% and permeability from 1265-2102 mD. Seismic interpretation established the presence of both synthetic and antithetic faults. A total of six synthetic and four antithetic faults were interpreted from the study area. Horizons interpretation was done both in the strike and dip directions. Time and depth structure maps revealed reservoir closures to be anticlinal and fault supported in the field. Hydrocarbon volumes were calculated using the deterministic (map-based) approach. Stock tank oil initially in place (STOIIP) for the proven oil column estimated for the D-04 reservoir was 11.13 MMSTB, 0.54 MMSTB for D-06, and 2.16 MMSTB for E-09A reservoir. For the possible oil reserves, a STOIIP value of 7.28 MMSTB was estimated for D-06 and 6.30 MMSTB for E-09A reservoir, while a hydrocarbon initially in place (HIIP) of 4.13 MMSTB of oil equivalents was derived for the undefined fluid (oil/gas) in D-06 reservoir. A proven gas reserve of 1.07 MMSCF was derived for the D-06 reservoir. This study demonstrated the effectiveness of 3-D seismic and well logs data in delineating reservoir structural architecture and in estimating hydrocarbon volumes

Impact of physical properties on material balance calculations: case study AL-Nasr oil field, Shabwah Governorate

The accuracy of many petroleum engineering calculations (e.g., material balance calculations, reserve estimation, well test analysis, advanced production data analysis, nodal analysis, surface network modeling, surface separation, and numerical reservoir simulations) largely depends on the accuracy of the data on pressure, volume, and temperature (PVT). An approach to improve the material balance calculation method is presented in this study. To achieve the objective, PVTP and MBAL Software programs were applied. PVT model was built by different methods. Software was implemented to calculate stock-tank oil, initially in place (STOIIP), using different approaches. Sensitive analysis was performed to investigate the effect of different parameters on material balance calculation. Illustration of the proposed approach was done on the data obtained from AL-Nasr oil field. The Average absolute error of PVT properties such as bubble-point pressure, relative volume, oil formation volume factor, Solution gas oil ratio and oil density is used to compare between actual and calculated values. Results showed a good agreement. History production (cumulative oil production, cumulative gas production, cumulative water production) were also calculated to investigate the match between history parameters and calculated parameters. Results indicated that the impact of PVT errors on material balance calculations can be significant.

Evaluation of Hydrocarbon Reserve in AD Field, Offshore Niger Delta

This study was carried out to quantify uncertainty in the reserve estimate of hydrocarbon in the reservoirs of AD Field, offshore, Niger Delta. Three Dimensional (3D) seismic data and log suites of seven wells (AD1 to AD7), gamma ray, resistivity, neutron and bulk density logs, well deviation and checkshot data in AD Field acquired from companies in the area. Twelve faults (Fault1 to Fault12) were identified from seismic structural interpretation while Six hydrocarbon-bearing sand intervals (Sand A - F) were delineated from the petrophysical analysis. The sand intervals thin-out basin wards, suggesting a prograding sequence. The porosity of the sand intervals ranges between 0.19 and 0.32, implying good to excellent porosity. The water saturation values ranged from 0.19 to 0.39, indicates a prospective accumulation of hydrocarbon. Sand A reservoir had the largest accumulation of hydrocarbon in-place with hydrocarbon pore volume of 2343 106 Reserve Barrel (RB), Stock Tank Oil-Initially-In-Place (STOIIP) of 175 MMbbl and gas initially-in-place of 0.30 TCF. The coefficient of variation in the reserve estimates of the reservoirs ranged from 0.09 to 0.15 indicating very low uncertainty of substantial hydrocarbon reserve that could be exploited.

Seismic Attribute Analysis and 3D Model-Based Approach to Reservoir Characterization of “KO” Field, Niger Delta

Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (Sw) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs. Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (Sw) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs. [KO1]Sentence has been rephrased. [M.N.2]This verb does not make sense in this context and has made the sentence unclear. [KO3]Sentence has been rephrased

Using Low Salinity Waterflooding to Improve Oil Recovery in Naturally Fractured Reservoirs

Low salinity waterflooding is an effective technique to accelerate and boost oil recovery. The impact of this technique has been investigated widely in laboratories for various scales and rock typing, most of which have demonstrated a potential improvement in oil recovery. This improvement has been attributed to several chemical and physical interactions that led to a change in the wettability to become more water-wet, as well as a reduction in the residual oil saturation. Meanwhile, it is rare to find a discussion in the literature about the efficiency of low salinity flooding in naturally fractured reservoirs. Therefore, in this work, we investigate the potential advantages of this method in fractured reservoirs using numerical simulations. A new approach to estimate the weighting factor using a tracer model has been proposed to determine the brine salinity and, hence, its properties in the mixing region. We have also used the relative permeability curves as a proxy for any physical and chemical mechanisms which are not represented explicitly in the model. The simulation outcomes highlighted the advantage of low salinity waterflooding in fractured reservoirs. An increment in oil recovery by 10.7% to 13% of Stock Tank Oil Initially In Place (STOIIP) was obtained using the dual- and single-porosity model, respectively. Therefore, the low salinity waterflooding technique represents a promising low-cost, effective method in fractured reservoirs.

The effectiveness of low salinity waterflooding in naturally fractured reservoirs

Low Salinity (LoSal) waterflooding is a technique which promises to improve and enhance oil recovery. The method has been studied widely in the laboratories using various core plug samples of sandstones and carbonates. Most of the experimental outcomes have demonstrated the possibility of recovery increment in conventional reservoirs. Meanwhile, it is rare to find a discussion in these experiments about the effectiveness of LoSal waterflooding in naturally fractured reservoirs. In this paper, we investigate the potential benefits in fractured reservoirs using simulations.It is often reported from coreflood experiments that LoSal injection has the ability to alter the rock wettability and reduce residual oil saturations through chemical and physical interactions between the rock-oil-water system. Based on the published work, we have calculated relative permeability curves to represent the flow in regions flooded with LoSal water. This includes a qualitative representation of uncertainty. In this sense, the relative permeabilities are a proxy for any physical and chemical mechanisms which are not explicitly represented. The newly generated flow curves were applied to simulate LoSal waterflooding using a fine-scale model and a field scale model based on a fractured reservoir from the Middle East.The simulation results underline the benefits of LoSal whereby the oil recovery from fractured reservoirs can be increased. An additional benefit is the control of water production. The fine-scale modelling has provided an in-depth analysis and accurate estimation of the oil recovery without modelling artefacts or limitations, where an increment of (12–14)% of the Stock Tank Oil Initially In Place (STOIIP) were obtained under secondary and tertiary recovery scheme, respectively. The investigated scenarios demonstrated a sensitivity to the newly generated flow curves and how they affect the ultimate oil recovery. However, for the field scale model, a higher oil production rate has maintained during LoSal waterflooding up to 32 K BPD by the end of year fourteen compared with 25 K BPD in case of high salinity scenario, besides a reduction in the produced water by 35.7%. Therefore, the effectiveness of LoSal brine required a longer time frame to observe the improvements in the oil displacement or sweep efficiency.

The Buchan Field, Blocks 20/5a and 21/1a, UK North Sea

AbstractThe Buchan Oilfield is a large mature field, now suspended, located in the Moray Firth. The field is situated 153 km NE of Aberdeen in water depths of c. 122 m. The reservoir comprises an overpressured and fractured Upper Devonian–Early Carboniferous fluvio-lacustrine sandstone. Production was via high permeability channel sandstones and permeable faults and fractures. The Buchan Field was brought onto production in May 1981 by BP Petroleum Development Ltd via the Buchan Alpha semi-submersible floating production vessel (FPV). The oil column is c. 2000 ft in height with a matrix stock tank oil initially in place (STOIIP) range of 322–471–668 MMbbl. Production from the ten vertical development wells was driven by pressure depletion (over 5000 psi since first oil) coupled with weak aquifer influx. Production from the Buchan Field ceased on 13 May 2017 after having produced 147.8 MMbbl. The Buchan FPV was subsequently taken off-station during August 2017. A new facility or tie-back redevelopment option will be required to access the remaining resources which are in the range of 20–90 MMbbl depending on the STOIIP, the production mechanism and the potential development plan.

Reservoir Evaluation and Volumetric Analysis of Rancho Field, Niger Delta, Using Well Log and 3D Seismic Data

Exploration and exploitation for hydrocarbon are associated with a lot of complexities, it is therefore necessary to integrate available geologic models for accurate hydrocarbon prospecting and risk analysis. This study is aimed at determining the structural, petrophysical and volumetric parameters for reservoir evaluation within the Rancho field. 3D seismic data was used for evaluating the hydrocarbon potential of the field. A suite of well logs but not limited to gamma ray logs (GR), deep resistivity log (DRES), neutron log (NPHI) and density log (RHOB) from four (4) wells were employed in characterising dynamic properties of the reservoirs. The GR log was used in lithology identification while the resistivity log was used in identifying probable hydrocarbon bearing sands. A correlation exercise was carried out to identify lateral continuity and discontinuity of facies across the wells. Thereafter petrophysical parameters were analysed from the suite of wire line logs. Major faults were mapped on the 3D seismic data and identified hydrocarbon bearing sand tops from the well logs were mapped as horizons on the seismic section, maps were generated and volumetric analysis was done. Nine (9) hydrocarbon sands (Sands A - I) were identified within the study area. The well log revealed an alternation of sand and shale layers as well as shale layers increased in thickness with depth, while the sand bodies reduced in thickness with depth which characterized the Abgada Formation of the Niger Delta. The effective porosities of the sands range from 21% - 31%, the permeability ranges from 28% - 44%, 70% - 80% for the net to gross, volume of shale range from 14% - 40% and hydrocarbon saturation ranges from 63% - 82%. Twelve (12) faults were mapped within the study area and the structural styles revealed a fault assisted closures. The volumetric analysis showed that Sand F had Stock Tank Oil Initially In Place (STOIIP) of 5,050,000,000 bbls of oil and Sand G had STOIIP of 17,870,000,000 bbls, these sands are proposed to be developd because of the volume of oil in them and area covered by the reservoir, calculated Gross Rock Volume (GRV) of 29.5 km3 and 104.5 km3 respectively.

Ranking of geostatistical models and uncertainty quantification using Signal Detection Principle (SDP)

The selection of an optimal model from a set of multiple realizations for dynamic reservoir modelling and production forecasts has been a persistent issue for reservoir modelers and decision makers. Current evidence has shown that many presumably good reservoir models which originally matched the true historic data did not always perform well in predicting the future of the reservoir as a result of uncertainties.In this paper, a new method for optimal model selection using Signal Detection Principle (SDP) approach is presented. In principle, SDP approach models the dissimilarity between various realizations as a cross-function of spatial distance, statistical correlation and the inherent noise level in the model; while the existing methods estimate the dissimilarity between parameter values of different realizations as a function of distance (statistical or spatial distance) or quality factor. SDP approach fills the model divergence gap by way of classifying the information-bearing patterns in a model as signals, and identifying random patterns which bears no information as noise. Thus, it quantifies the mismatch uncertainty and the inherent fudge in every realization as a measure of the model's reliability. The SDP approach has been validated with historical data, and the results show that the reliability factor of the best model has a value of one. Thus, if the strongest reservoir model has a reliability factor of one, then that model will make approximately the closest and best predictions as the true system in every forecast; whereas if the reliability factor of the model is less than or greater than one, its predictions will always disperse from historical data and is unsuitable for reservoir forecasts. Two examples based on real field data are used to demonstrate the application of SDP approach. In these case examples SDP was used to analyse the difference between the reservoir models in a set of multiple realizations. The target variable in this study was STOIIP (Stock Tank Oil Initially in Place). The results show that the models with a lower reliability factor made similar predictions as the real reservoir data in almost all the forecasts. Similarly, the models with higher reliability factors made dissimilar and more unreliable predictions in most of the forecasts.

Prospect Analysis and Hydrocarbon Reservoir Volume Estimation in an Exploration Field, Shallow Offshore Depobelt, Western Niger Delta, Nigeria

The daunting challenge in the exploration and production of oil and gas in the face of continual rise in the world’s energy consumption has long been how to economically recover bypassed reserves within existing assets. This research is focused on the analysis of prospects and volumetric estimation of the hydrocarbon reservoirs delineated within an exploratory field using 3D seismic data and suites of wireline logs. The prospectivity of the delineated reservoir was carried out using seismo-structural interpretation and formation evaluation towards the assessment of the prolific hydrocarbon occurrence within the field. The reservoirs have porosity (0.29–0.32) for H1, (0.20–0.31) for H2 and (0.30–0.40) for H3 and the average computed hydrocarbon saturation of (0.31–0.62) for H1, (0.16–0.52) for H2 and (0.64–0.73) for H3, hydrocarbon pore volume (HCPV) of 28,706.95, 33,081.2 and 45,731.49 barrels for H1, H2 and H3, respectively, while the estimated stock tank oil initially-in-place (STOIIP) range (136.8–140.73) MMSTB for H1, (36.77–489.64) MMSTB for H2 and (166.62–308.14) MMSTB for H3. The observed porosity and hydrocarbon saturation for the delineated reservoirs as well as the estimated hydrocarbon pore volume and storage total oil in place indicate that the reservoirs are highly prolific. The study has therefore contributed to the understanding of hydrocarbon resource potential within the study area.

Uncertainty in attribute-based inversion for quantification of the estimation of stock-tank oil initially in place in Kalol reservoir, Cambay Basin, India

Uncertainty is not an inherent feature of a reservoir; it is the result of lack of knowledge and understanding about the reservoir. Uncertainty can be modeled, but there is no objective measure of uncertainty. All geostatistical methods used in estimation of reservoir parameters are inaccurate; hence, modeling of “estimation error” in the form of uncertainty analysis is important. Uncertainty is associated with each process involved in geologic modeling, including data acquisition, data processing, interpretation, structural modeling, facies modeling, petrophysical modeling, and volume estimation, which affects the ability to understand the reservoir behavior and make reliable production forecasts and risk-free decisions. Hence, uncertainty analysis is a prerequisite measure for initial calculation of oil in place in any field. In the estimation of stock-tank oil initially in place (STOIIP) in Kalol reservoir, Cambay Basin, India, a geologic uncertainty study was initiated to identify and quantify the input parameters of greatest impact in the reservoir model. Results showed that the structural uncertainty has maximum impact and volume expansion factor has minimum impact in the estimation of stock-tank oil initially in place, whereas lithologic and petrophysical uncertainties have equal impact. Hence, during structural, facies, and petrophysical modeling, one has to take special precaution before finalizing the reserve calculation. Therefore, uncertainty and sensitivity analysis in the estimate of stock-tank oil initially in place should be applied on a routine basis because it greatly helps in improving fluid estimate from the field and ultimately the economics of the investments.

A New Strategy Explores Tight Oil/Gas Reservoirs: Fit-for-Purpose Acid Fracturing

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 164778, ’A New Strategy To Explore Tight Oil/Gas Reservoirs: Fit-for- Purpose Acid Fracturing,’ by G.M. Hegazy, SPE, and Adel M. Salem, American University in Cairo and Suez University; Shedid A. Shedid, British University in Egypt; Shouhdi E. Shalaby, Suez University; and J. Abbott, Schlumberger, prepared for the 2013 North Africa Technical Conference and Exhibition, Cairo, 15-17 April. The paper has not been peer reviewed. As oil companies have moved to more-marginal reservoir targets, application of conventional techniques has often yielded disappointing results, and tighter zones are often abandoned for more-promising target intervals. Marginal reservoirs may require horizontal-well drilling or multiple-stage hydraulic fracturing to achieve economic production targets. In an effort to reduce risks and costs associated with these alternative processes, a new stimulation strategy has been adopted for tight intervals using vertical wells before going to horizontal wells. Resources Availability There are tens of undeveloped reservoirs and even undiscovered plays/prospects in the area of this study (Abu Dhabi). These new plays and undeveloped reservoirs contain huge quantities of stock-tank oil initially in place (STOIIP). Most of these reservoirs are still in the appraisal phase, and tremendous efforts are required to bring the best reservoirs to the top of the development portfolio. The decision to transfer a single reservoir from appraisal to development mostly depends on STOIIP ranking, which in turn takes into account the following factors. Exploration-, Appraisal-, and Development-Data Investigation. The study investigates 51 reservoirs allocated with-in 14 fields under the appraisal portfolio, and three exploration reservoirs dis covered recently after applying the new concept of fit-for-purpose acid fracturing. The work is extended to include a development reservoir in which long-horizontal-well drilling is implemented while the study recommends fracturing implementation. Fig. 1 illustrates the distribution of STOIIP percentage among the three phases of exploration, appraisal, and development. The investigation of well-test results shows that more than 180 wells were tested in the area of the study. For 98 wells, the test results were considered inconclusive because of either reservoir tightness or improper stimulation treatment, or both. Reservoir Ranking by STOIIP. On the basis of STOIIP ranking results, 13 reservoirs out of a total of 54 were ranked highly, with a minimum of 100 million STB. These reservoirs represent 77% of the total STOIIP of the portfolio. Not all of these high-STOIIP reservoirs could produce with matrix-stimulation treatment, however, because the permeability of 12 reservoirs is less than 4 md. In the class of reservoirs ranging between 100 and 50 million STB, 17 reservoirs represent some 17% of the total STOIIP of the portfolio. The remaining reservoirs are very small, with STOIIP values of less than 50 million STB.