New reservoir model from an old oil field: Garfield conglomerate pool, Pawnee County, Kansas

AAPG Bulletin ◽  
2007 ◽  
Vol 91 (10) ◽  
pp. 1349-1365 ◽  
Author(s):  
James P. Rogers
Keyword(s):  
Oil Field ◽  
Reservoir Model ◽  
New Reservoir

Uncertainty Analysis of a Giant Oil Field in the Middle East Using Surrogate Reservoir Model

2006 ◽  
Author(s):  
Shahab D. Mohaghegh ◽  
Hafez H. Hafez ◽  
Razi Gaskari ◽  
Masoud Haajizadeh ◽  
Maher Kenawy
Keyword(s):  
Middle East ◽  
Uncertainty Analysis ◽  
Oil Field ◽  
Reservoir Model

Research on Applied Mechanics with Reservoir Interwell Dynamic Connectivity Model and Inversion Method in Case of Shut-In Wells

2014 ◽  
Vol 540 ◽  
pp. 296-301 ◽  
Author(s):  
Zhi Jiang Kang ◽  
Hui Zhao ◽  
Hui Zhang ◽  
Yun Zhang ◽  
Ying Li ◽  
...  
Keyword(s):  
Oil Field ◽  
Inversion Method ◽  
Applied Mechanics ◽  
Practical Application ◽  
Reservoir Model ◽  
Connectivity Model ◽  
Interwell Connectivity ◽  
And Inversion ◽  
Novel Model ◽  
Dynamic Connectivity

Due to the limitations that the current interwell connectivity can not consider shut-in wells and the inversion solving method is not reliable, a novel model that can consider the compressibility and shut-in situations is established. In order to further decrease the ill-posedness of the solutions for the connectivity model, a constraint optimization algorithm by using Bayesian theories and projection gradient method are proposed. The tests for a synthetic reservoir model and a real oil field indicate that the proposed methodology can efficiently estimate the interwell connectivity with high precision and reliability for practical application.

scholarly journals Reservoir Model and Production Strategy of Mishrif Reservoir-Nasryia Oil Field Southern Iraq

2020 ◽  
Vol 10 (3) ◽  
pp. 54-85
Author(s):  
Hamzah Amer Abdulameer ◽  
Dr. Sameera Hamd-Allah
Keyword(s):  
Oil Recovery ◽  
Carbonate Rock ◽  
History Matching ◽  
Water Saturation ◽  
Oil Field ◽  
Neutron Density ◽  
Reservoir Model ◽  
Water Contact ◽  
Medium Permeability ◽  
Production Strategy

Nasryia oil field is located about 38 Km to the north-west of Nasryia city. The field was discovered in 1975 after doing seismic by Iraqi national oil company. Mishrif formation is a carbonate rock (Limestone and Dolomite) and its thickness reach to 170m. The main reservoir is the lower Mishrif (MB) layer which has medium permeability (3.5-100) md and good porosity (10-25) %. Form well logging interpretation, it has been confirmed the rock type of Mishrif formation as carbonate rock. A ten meter shale layer is separating the MA from MB layer. Environmental corrections had been applied on well logs to use the corrected one in the analysis. The combination of Neutron-Density porosity has been chosen for interpretation as it is close to core porosity. Archie equation had been used to calculate water saturation using corrected porosity from shale effect and Archie parameters which are determined using Picket plot. Using core analysis with log data lead to establish equations to estimate permeability and porosity for non-cored wells. Water saturation form Archie was used to determine the oil-water contact which is very important in oil in place calculation. PVT software was used to choose the best fit PVT correlation that describes reservoir PVT properties which will be used in reservoir and well modeling. Numerical software was used to generate reservoir model using all geological and petrophysical properties. Using production data to do history matching and determine the aquifer affect as weak water drive. Reservoir model calculate 6.9 MMMSTB of oil as initial oil in place, this value is very close to that measured by Chevron study on same reservoir which was 7.1 MMMSTB. [1] Field production strategy had been applied to predict the reservoir behavior and production rate for 34 years. The development strategy used water injection to support reservoir pressure and to improve oil recovery. The result shows that the reservoir has the ability to produce oil at apparently stable rate equal to 85 Kbbl/d, also the recovery factor is about 14%.

Well location optimization of Zama reservoir using top down reservoir modeling(TDRM)

2020 ◽  
Author(s):  
Taehun Lee ◽  
Kyungbook Lee ◽  
Hyunsuk Lee ◽  
Wonsuk Lee
Keyword(s):  
Artificial Intelligence ◽  
Human Life ◽  
Oil Field ◽  
Oil Fields ◽  
Reservoir Modeling ◽  
Reservoir Model ◽  
Location Optimization ◽  
Well Location ◽  
Artificial Intelligence Technology ◽  
Short Time

<p>Artificial intelligence is applied in various fields of human life and is being actively studied and applied in the oil fields. Especially, the digital oil field, which has recently been spotlighted, is required to simulate the reservoir using artificial intelligence. However, there is almost little research to date. Therefore, in this study, we applied TDRM using artificial intelligence technology to Zama field located on the land of Canada. The required static and dynamic data were obtained from Accumap, a Canadian well information S/W. As a result, the reservoir model was constructed successfully and the well location optimization could be performed in a short time using TDRM.</p>

scholarly journals Safah field, Oman: retrospective of a new-concept exploration play, 1980 to 2000

GeoArabia ◽  
2003 ◽  
Vol 8 (3) ◽  
pp. 367-430 ◽  
Author(s):  
David R.D. Boote ◽  
Duenchien Mou
Keyword(s):  
History Matching ◽  
Management Strategies ◽  
Oil Field ◽  
High Porosity ◽  
Reservoir Model ◽  
The South ◽  
Reservoir Architecture ◽  
The North ◽  
Early Tertiary ◽  
Concept Exploration

ABSTRACT The Safah oil field was discovered in 1983 on the north-plunging Lekhwair Arch of northwest Oman. The arch lacks any significant structural closure and the accumulation is stratigraphically trapped within chalky high porosity-low permeability Upper Shu’aiba carbonates of mid-late Aptian age. The complexity of its trapping geometry, internal reservoir architecture, reservoir quality and hydrocarbon charge history precluded easy explanation and geological models used to describe the field evolved quite significantly over time to accommodate new data and changing regional perspectives. These had a profound influence, first upon the decision to test what was a speculative new concept exploration prospect and later during appraisal and development, in defining an optimum static reservoir model, history matching and efficient field management strategies. The original play concept developed out of a loosely constrained regional structural and stratigraphic synthesis. Early isopach mapping had identified an enormous paleohigh on the North Lekhwair Arch, which appeared well placed to receive charge in the later Cretaceous and early Tertiary. This was tilted northward during the late Miocene, when any structurally trapped oil or gas must have been spilled to the south. However, nearby analogs suggested that the northeastern margin of the Upper Shu’aiba intraplatform Bab Basin crossed the arch in the vicinity of the paleohigh and it seemed possible that remigrating hydrocarbons might have been stratigraphically trapped against the impermeable basinal facies equivalents of Shu’aiba platform carbonates. Safah-1x was drilled to test this hypothesis, just to the north of the weakly defined Upper Shu’aiba shelf break. It encountered a thin pay zone at the northern end of what proved to be a more than 1 billion barrels STIIOP accumulation. The complexity of the field became increasingly apparent during appraisal drilling. Both differentiated shelf-to-basin and layered mid-shelf ramp depositional models were proposed to describe its unexpectedly heterogeneous internal reservoir architecture. Independent petrographic, fluid property and oil isotope analyses seemingly contradicted more likely stratigraphic correlations and consensus on a static reservoir model proved difficult to reach. As a result, geologically simple layered reservoir descriptions were favored during the early development of the field. However, as the regional perspective improved with better local analogs and increasing amounts of well and seismic data, attention eventually refocused back toward a more sophisticated stratigraphic explanation. The reservoir is now interpreted to be a low-energy mid-Shu’aiba highstand composite sequence with younger lowstand shales and offlapping carbonate shoals to the south. The updip trapping mechanism is far more complex than originally anticipated, formed by discontinuities between the porous lowstand shoals. The enigmatic relationship between stratigraphic architecture and in-reservoir PVT fluid properties and d13C isotope gradients appear to reflect dual charging by a high GOR Jurassic-sourced oil during the late Cretaceous-early Tertiary and low GOR Silurian oils in the Miocene. Internal stratigraphic baffles prevented complete homogenization and the PVT and isotope gradients remain as geochemical palimpsests. This resolution of initially rather contradictory observations was achieved by synthesizing data into a coherent narrative logic, most consistent with the available geological information at all scales, from the regional and general to the local and specific. Although more advanced seismic, petrographic and geochemical technologies certainly encouraged increasingly precise interpretations, the issues they raised were still geological and so still most effectively utilized within the context of such narratives. Ultimately, it was only by assessing these against broader geological perspectives that it proved possible to judge the validity of in-field interpretations with any confidence.

scholarly journals Refining Permeability Values for History-Matching of the Reservoir Simulation Model

2020 ◽  
Vol 20 (3) ◽  
pp. 223-230
Author(s):  
Margarita A. Smetkina ◽  
◽  
Oleg A. Melkishev ◽  
Maksim A. Prisyazhnyuk ◽  
◽  
...  
Keyword(s):  
Reservoir Simulation ◽  
History Matching ◽  
Simulation Models ◽  
Data Interpretation ◽  
Well Logging ◽  
Initial Permeability ◽  
Oil Field ◽  
Statistical Characteristics ◽  
Reservoir Model ◽  
Porosity And Permeability

Reservoir simulation models are used to design oil field developments, estimate efficiency of geological and engineering operations and perform prediction calculations of long-term development performances. A method has been developed to adjust the permeability cube values during reservoir model history-matching subject to the corederived dependence between rock petrophysical properties. The method was implemented using an example of the Bobrikovian formation (terrigenous reservoir) deposit of a field in the Solikamskian depression. A statistical analysis of the Bobrikovian formation porosity and permeability properties was conducted following the well logging results interpretation and reservoir modelling data. We analysed differences between the initial permeability obtained after upscaling the geological model and permeability obtained after the reservoir model history-matching. The analysis revealed divergences between the statistical characteristics of the permeability values based on the well logging data interpretation and the reservoir model, as well as substantial differences between the adjusted and initial permeability cubes. It was established that the initial permeability was significantly modified by manual adjustments in the process of history-matching. Extreme permeability values were defined and corrected based on the core-derived petrophysical dependence KPR = f(KP) , subject to ranges of porosity and permeability ratios. By using the modified permeability cube, calculations were performed to reproduce the formation production history. According to the calculation results, we achieved convergence with the actual data, while deviations were in line with the accuracy requirements to the model history-matching. Thus, this method of the permeability cube adjustment following the manual history-matching will save from the gross overestimation or underestimation of permeability in reservoir model cells.

RESERVOIR CHARACTERISATION OF THE TOOLACHEE UNIT 'C' IN THE MOOMBA/BIG LAKE AREA: FOCUSSING ON MINIMISING RISK

1995 ◽  
Vol 35 (1) ◽  
pp. 92
Author(s):  
S.l. Mackie ◽  
C.A. Grasso ◽  
S.R. McGuire
Keyword(s):  
Field Performance ◽  
Depositional Environments ◽  
Oil Field ◽  
Lake Area ◽  
Reservoir Model ◽  
Attribute Analysis ◽  
Net To Gross ◽  
Gippsland Basin ◽  
First Time ◽  
3D Seismic Data

Mackerel, the third largest oil field in the Gippsland Basin, is a mature field with over 80 per cent of reserves produced from 18 original development wells.The initial Mackerel development was based on a fairly simplistic reservoir model incorporating the results of the four exploration wells. The net to gross was anticipated at 90 per cent throughout the reservoir and no significant permeability barriers were expected. After 10 years of production a review of field performance indicated the reservoir was not as homogenous as first anticipated.Redevelopment of the Mackerel Field began in 1990 following the acquisition of the first of two high resolution 3D surveys and culminated in the drilling of 18 additional wells from the Mackerel platform during 1993 and 1994. It was these 3D surveys which changed the entire reservoir model of Mackerel to one of a far more compartmentalised nature.Seismic attribute analysis, when calibrated to 2D forward modelling was used to predict intra-reser- voir seals and the distribution of poorer quality reservoir; both not previously recognised over the field. The truncation points of the intra-reservoir seals against the main field-wide trapping unconformity were accurately mapped using seismic attributes and image enhancement techniques such as ER Mapper. Previously undetectable fault extensions, with throw around 10 m, can act as partial flow barriers and were recognised for the first time via 'sun-angle illumination' of azimuth maps. This allowed optimum well placement and helped explain historical field performance. Horizon slicing techniques and the calibration of volume attributes were used to establish depositional environments and seal capacity of the predicted intra-reservoir seals.The drilling results have shown that over the production life of the Mackerel Field the reservoir consists of a number of drainage compartments, each separated by seismically resolvable intra-res- ervoir seals.The redevelopment of the Mackerel field increased production rate by 18 thousand barrels per day (kBD) in 1993, and proved additional capture reserves of which approximately 40 percent can be directly attributed to the 3D seismic data and the applied interpretation techniques.

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