scholarly journals Analisa Dan Optimasi Recovery Perolehan Cadangan Gas Dengan Melihat Parameter Design Sumur Pada Struktur Musi Barat Di Lapangan Riyadh

2017 ◽  
Vol 6 (2) ◽  
pp. 14-24
Author(s):  
Rycha Melysa ◽  
Idham Khalid

Lapangan Riyadh merupakan lapangan yang memiliki potensi cadangan gas. Berdasarkan hasil perkiraan cadangan secara volumetric lapangan Riyadh memiliki cadangan sebesar 686.334 Bcf. Lapangan Riyadh ini memiliki 28 sumur yaitu hanya 20 sumur yang berproduksi hingga tahun 2016. Perolehan gas pada lapangan Riyadh hingga akhir tahun 2016 yaitu sebesar 505.336 Bcf. Maka perlu dilakukan perkiraan cadangan berdasarkan material balance dan melakukan optimasi recovery perolehan gas sesuai dengan design sumur di lapangan riyadh. Pada lapangan Riyadh ini dilakukan analisa forecast tekanan terhadap kumulatif produksi gas untuk mengetahui tekanan pada kumulatif produksi gas terhadap waktu. Selanjutnya dilakukan perhitungan perkiraan cadangan dengan metode plot P/z vs Gp dan dilakukan identifikasi driving mechanism. Dari hasil perkiraan cadangan dapat dihitung perkiraan recovery factor current dan recovery factor predict . tahap optimasi recovery perolehan gas dilakukan dengan prosper dan mbal software. Hasil perkiraan cadangan gas dengan material balance plot P/z vs Gp sebesar 702.895 Bcf. Analisa plot P/z vs Gp dapat diketahui bahwa reservoir pada lapangan Riyadh dipengaruhi aquifer influx sehingga dapat di indikasi dari hasil metode cole plot, driving mechanism lapangan Riyadh ini adalah strong water drive .kemudian dari hasil perhitungan cadangan plot P/z vs Gp untuk RF current sebesar 72 % dengan RF prediksi 82 % berdasarkan manual. Setelah dilakukan simulasi Mbal recovery perolehan gas pada lapangan Riyadh dapat di optimasi sampai 85 % berdasarkan parameter design sumur yaitu tubing 3 inch.

2002 ◽  
Vol 5 (01) ◽  
pp. 49-59 ◽  
Author(s):  
J.L. Pletcher

Summary Experience with material-balance data sets from the field and from simulation has revealed some procedures that can be used to improve analysis of both oil and gas reservoirs:Failure to account for a weak waterdrive can result in significant material-balance errors.The assertion of previous authors that weak waterdrive exhibits a negative slope on the Cole (gas) and Campbell (oil) plots has been confirmed. A weak waterdrive is much more unambiguous on these plots than on commonly used plots, such as the p/z plot for gas.A modified version of the Cole plot is proposed to account for formation compressibility.The reservoir drive indices are a useful tool for determining the correctness of the material-balance solution because they must sum to unity. The drive indices should never be normalized to sum to unity because this obscures their usefulness and leads to a false sense of security.A modified version of the Roach plot (for gas) is proposed that improves interpretation in some waterdrive situations.Material balance has not been replaced by reservoir simulation; rather, it is complementary to simulation and can provide valuable insights to reservoir performance that cannot be obtained by simulation. Introduction Classical material balance is one of the fundamental tools of reservoir engineering. Many authors have addressed the difficult problem of solving the material balance in the presence of a waterdrive (Refs. 1 through 5 are just a few of the more significant ones). The emphasis in the literature has been on strong and moderate waterdrives. In this paper, examples of weak waterdrives are shown in which the effects on the material balance are significant. All aquifers studied here are of the "pot aquifer" type, which is time-independent. In gas reservoirs, the plot of p/z vs. cumulative gas production, Gp, is a widely accepted method for solving the gas material balance1 under depletion-drive conditions. Extrapolation of the plot to atmospheric pressure provides a reliable estimate of original gas in place (OGIP). If a waterdrive is present, the plot often appears to be linear, but the extrapolation will give an erroneously high value for OGIP. Many authors have addressed this problem (including those in Refs. 2 and 5 through 8), especially in cases of strong or moderate waterdrives. The p/z plot is actually more ambiguous in weak waterdrives than in strong or moderate ones. The Cole plot7,9 has proven to be a valuable diagnostic tool for distinguishing between depletion-drive gas reservoirs and those that are producing under a waterdrive. The analogous plot for oil reservoirs is the Campbell plot.10 The literature has emphasized strong and moderate waterdrives, the signature shapes of which are a positive slope and a hump-shaped curve, respectively, on these plots. Previous authors have recognized that weak waterdrives can produce negative slopes on these two diagnostic plots, but this author is not aware of any example plots in the literature. This paper shows examples, using simulation and actual field data, wherein a negative slope clearly reveals a weak waterdrive. These plots are much more diagnostic than the p/z plot. Once a weak waterdrive has been diagnosed, the appropriate steps can be taken in the material-balance equations to yield more accurate results. The Cole plot assumes that formation compressibility can be neglected, which is frequently the case with gas. However, in those reservoirs in which formation compressibility is significant, a modification to the Cole plot is presented that incorporates formation compressibility and gives more accurate results. The reservoir drive indices have been used to quantify the relative magnitude of the various energy sources active in a reservoir. It is shown here that the drive indices are also a useful diagnostic tool for determining the correctness of a material balance solution because they must sum to unity. If they do not sum to unity, a correct solution has not been obtained. In some commercial material-balance software, the drive indices are automatically normalized to sum to unity, which not only obscures their usefulness but also leads to the false impression of having achieved a correct solution. The Roach plot has been presented11 as a tool for solving the gas material balance when formation compressibility is unknown, with or without the presence of waterdrive. This paper shows that for waterdrives that fit the small pot aquifer model, incorporating cumulative water production into the x-axis plotting term improves the linearity of the Roach plot and gives more accurate values for OGIP. Finally, it is argued that even in those reservoirs for which a simulation study is performed, classical material-balance evaluation should be performed on a stand-alone basis. Simulation should not be viewed as a replacement for material balance because the latter can yield valuable insights that can be obscured during simulation. Performing a separate material balance study usually will improve overall reservoir understanding and enhance any subsequent simulation study. Material balance should be viewed as a complement to simulation, not as a competing approach. In this paper, formation compressibility, cf, is assumed to be constant and unchanging over the reservoir life under investigation. References are given for recommended methods to be used in those cases in which cf is variable.


KURVATEK ◽  
2018 ◽  
Vol 3 (2) ◽  
pp. 55-65 ◽  
Author(s):  
Sudarmoyo Gunanto ◽  
Avianto Kabul Pratiknyo ◽  
Sigit Priyanto
Keyword(s):  

Lapangan gas “MC” reservoir “SDM” terletak dibagian barat blok Sumatera Selatan.  Reservoir “SDM” telah diproduksi oleh 4 sumur, mulai produksi  Juli 1987. Kumulatif produksi gas per 31-01- 2017 adalah  38.771 MMSCF. Perusahaan bermaksud membuat rencana pengembangan lanjut lapangan (POFD) dalam  rangka untuk mengoptimalkan  perolehan gas. Permasalahan utamanya adalah berapa cadangan gas per 31-01-2017. Data teknik pendukung untuk  prediksi  cadangan gas, seperti data reservoir, produksi, karakteristik gas fungsi waktu  telah dicatat oleh perusahaan sejak lapangan “MC” mulai berproduksi, termasuk data cadangan gas mula-mula volumetrik. Metodologi yang digunakan, pertama mengumpulkan data teknik pendukung, kedua analisa perilaku reservoir, ketiga menentukan tekanan reservoir rata-rata  menggunakan tiga model tekanan rata-rata (sumuran, area dan volume),  keempat  menentukan faktor kompresibilitas gas (Z) menggunakan  tujuh  model faktor kompresibilitas Z (metode Standing & Katz, Thomas Hankinson Phillips, Soave Redlich Kwong, Beggs & Brill, Dranchuk Abu Kassem, Peng-Robinson, dan M.A. Mahmoud), kelima menentukan jenis mekanisme pendorong dengan Metode Cole Plot , keenam   menentukan Original Gas In Place (OGIPi) dan  Ultimate Recovery (URi) berdasarkan  pendekatan  Material Balance P/Z , ketujuh  prediksi Cadangan Gas per 31-01-2017. Hasilnya adalah cadangan gas per 31-01-2017  reservoir “SDM” sebesar 7.200 MMSCF setelah divalidasi dengan cadangan gas per 31-01-2017 volumetrik. Kata kunci: tekanan reservoir, rata-rata, faktor Z, cadangan sisa gas.


2021 ◽  
Author(s):  
Handita Reksi Dwitantra Sutoyo ◽  
Diniko Nurhajj ◽  
Anak Agung Iswara Anindyajati ◽  
Dwi Hudya Febrianto ◽  
Nova Kristianawatie

Abstract Early production of gas reservoirs is usually associated with a volumetric gas driving mechanism with no water production. Aquifer activity is minimal as well during the early life of the reservoir. In this paper, we will discuss about the good engineering practices based on several shut-in pressure data to observe and maximize marginal gas field value. We will also discuss about the possibility of water drive behavior in this field. Shut-in pressure data plays an important role in determining the in-place and reservoir dynamics of the gas reservoir. High shut-in pressure usually indicates high gas reserves. On the other hand, it shows a very strong water drive existence. The study takes place on a sandstone gas reservoir with an abnormal pressure regime on it. Production performance was then analyzed using the rate transient analysis (RTA) to determine its properties and gas in place and crosschecked with shut-in pressure data. From these steps, we can determine the trend of both static and flowing material balance (FMB) analysis to predict the reservoir dynamics. During the early life of production, it is clear that volumetric reservoir plays an important role in the reservoir dynamics since it produces no reservoir water. However, after 1 year of production, it starts to produce reservoir water. Monitoring starts when the first shut-in pressure shows a quite unexpected value. It puts a sense of both high gas reserves and aquifer activity. After applying all the pressure and production data on FMB and p/Z plot, it shows that both high gas reserves and aquifer activity exist in this field. The results of this study change the development strategy of this field, preventing doing major investment on high capital expenditure (CAPEX) with low results due to high aquifer activity. We can conclude that good reservoir monitoring and analysis combining several analytical methods can enhance our insight into reservoir dynamics. Combining FMB and p/Z, geologist starts to compare aquifer volume based on geological data and found to be similar with the results coming from analytical data. 3D reservoir simulation also confirms similar results based on those analyses.


2013 ◽  
Vol 2 (2) ◽  
pp. 24-27
Author(s):  
Novrianti Novrianti

Water Influx adalah air yang merembes ke dalam reservoir. Water Influx terjadi untuk mengimbangi gejala penurunan tekanan yang terjadi di reservoir karena masuknya air berfungsi untuk menggantikan minyak yang diproduksikan. Water Influx perlu diperhatikan untuk mengetahui luas aquifer serta pengaruhnya terhadap tingkat perolehan ( recovery factor). Lapangan X mulai produksi tahun 1955 dan injeksi air mulai dilakukan tahun 1974. Estimasi perhitungan Water influx pada lapangan X dilakukan dengan menggunakan persamaan  material balance dan metode Hurst – Van Everdingen. Selain menentukan Water influx metode Hurst – Van Everdingen juga berfungsi untuk menentukan bentuk dan luas aquifer. Kumulatif water influx yang diperoleh dengan menggunakan Metode Material Balance adalah 30 MMMSTB  sedangkan dengan metode Hurst – Van Everdingen adalah 32 MMMSTB. Bentuk aquifer lapangan X adalah  finite aquifer dengan rD = 8  dan Luas aquifer lapangan  X adalah 241016,62 ft.


2021 ◽  
Vol 2 (2) ◽  
pp. 68
Author(s):  
Indah Widiyaningsih ◽  
Panca Suci Widiantoro ◽  
Suwardi Suwardi ◽  
Riska Fitri Nurul Karimah

The RF reservoir is a dry gas reservoir located in Northeast java offshore that has been produced since 2018.  The RF reservoir has produced 2 wells with cumulative production until December 2019 is 31.83 BSCF. In January 2018 the gas production rate from the two wells was 36 MMSCFD and the reservoir pressure at the beginning of production was 2449.5 psia, peak production occurred in April 2019 with a gas flow rate of 98 MMSCFD but in December 2019 the gas production rate from both wells decreased to 30 MMSCFD with reservoir pressure decreased to 1607.8 psia. Changes in gas flow rate and pressure in the RF reservoir will affect changes in reservoir performance, so it is necessary to analyze reservoir performance to determine reservoir performance in the future with the material balance method. Based on the results the initial gas in place (IGIP) is 80.08 BSCF. The drive mechanism worked on the RF reservoir until December 2019 was a depletion drive with a recovery factor up to 88% and a current recovery factor (CRF) is 40%. The remaining gas reserves in December 2019 is 39 BSCF and the reservoir will be made a production prediction until December 2032. Based on production predictions of the four scenarios, scenario 2 was chosen as the best scenario to develop the RF reservoir with a cumulative production is 66.1 BSCF and a recovery factor of 82.6%.


Author(s):  
C. G. J. Nmegbu ◽  
Orisa F. Ebube ◽  
Emmanuel Aniedi Edet

The purpose of this research work is to comparatively study the oil recovery factor from two major aquifer geometry (Bottom and Edge water aquifer) using water aquifer model owing to the fact that most if not every reservoir is bounded by a water aquifer with relative size content (Most Large). These aquifers are pivotal in oil recovery factor (percent%), Cumulative oil produced (MMSTB) as well as overall reservoir performance the methodology utilized in this study involves; Identification of appropriate influx models were utilized for aquifer characterization. The characterizes of the Niger Delta reservoir aquifer considered include aquifer permeability, aquifer porosity etc. Estimation of aquifer properties is achieved by using regressed method in Material Balance Software (MBAL). This approach involves History Matching of average reservoir pressure with computed pressure of the reservoir utilizing production data and PVT data. The computed pressure from model is history matched by regressing most uncertain parameters in aquifer such as aquifer size, permeability, and porosity. Historic production data was imputed into the MBAL Tank Model, the production data was matched with the model simulation by regressing on rock and fluid parameters with high uncertainty. The match parameters were recorded as the base parameter and other sensitivity on aquifer parameters using the Fetkovich model for the bottom and edge water drive. The average percentage increase in oil cumulative volume was 0.40% in fovour of bottom water drive. Further sensitivity on cumulative oil recovered showed the increase in reservoir size with increasing aquifer volumes increases oil production exponentially in bottom water drive whereas edge water drive increased linearly. Aquifer volume, aquifer permeability showed linear relationship with bottom and edge water drive.


2021 ◽  
Vol 9 ◽  
Author(s):  
Zhiyu Xi ◽  
Na Jia ◽  
Ezeddin Shirif

Due to the diversity of alkali categories and reservoir conditions, the varied oil recovery driving mechanism of alkaline flooding is subjected to different types of emulsion generation. In this study, a modified bottle test method that assesses major emulsion type formation for preliminary prediction of alkaline flooding performance in oil recovery is introduced. The modified method considers the necessary energy input required for mixing immiscible bulk phases at low interfacial tension (IFT) regions to improve the representativity of emulsion formation in the bottle test to that of in porous media. To accurately evaluate the emulsion type and phase volume distribution from the bottle test, each emulsion phase after aging in the test bottle was sampled and its water content was measured through Karl Fischer titration. Afterward, material balance calculations other than pure volume observation were applied to quantify the emulsion volume and determine the major emulsion type formation. It is found that the majority of emulsion effluent type from the sandpack flooding test were in agreement with the bottle test forecast which proved the feasibility of the modified bottle test method. The statistically optimized experimental designs were implemented due to the simplicity of the new bottle test method and it considerably cut the time expense regarding the alkaline flooding performance prediction. The high versatility of the modified bottle test ensures that the alkali usage is not limited to the inorganic alkalis mentioned in this study; other type of alkaline solutions can also be used for further expanding the scope of its application.


PETRO ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 158
Author(s):  
Bonifasius Aristomo Haryo Adi ◽  
Onnie Ridaliani ◽  
Rida Husla

<p><em>The purpose of calculating the Original Oil In Place (OOIP) is to know the potential of reservoir to be produced. Calculation of OOIP in field Y based on determining the type of drive mechanism at the beginningfollowed by calculation the value of Underground Withdrawal and parameters of fluid expansion. All parameters then used to draw the graphic using Havlena and Odeh Method. The value of OOIP is </em>354,766 MMSTB<em>.</em></p><p><em>Along with the time and production activity, the OOIP will be reduced. Therefore it is important to forecast the production itself. Constant Decline is determined using Trial Error and X<sup>2</sup> Chisquare Test Method with value of constant decline b = 0 and decline rate 0,01855. This means that the type of decline curve is exponential curve. This type of decline curve is used to forecast the production until q economic limit. As a result, the value of Estimated Ultimated Recovery is 296,0386 MMSTB, Recovery Factor 83,4461%, and Remaining Reserve 51,9415 MMSTB</em>.<em></em></p><p align="center"> </p><p>Keyword: <em>Original Oil In Place</em>, <em>Decline Curve Analysis, material balance straight line, Recovery Factor, Remaining Reserve</em></p><p> </p>


Author(s):  
Tomi Erfando ◽  
Novia Rita ◽  
Romal Ramadhan

As time goes by, there will be decreasing of production rates of a field along with decreasing pressure. This led to the necessity for further efforts to increase oil production. Therefore, pressure support is required to improve the recovery factor. Supportable pressure that can be used can be either water flooding and polymer flooding. This study aims to compare recovery factor to scenarios carried out, such as polymer flooding with different concentrations modeled in the same reservoir model to see the most favorable scenario. The method used in this research is reservoir simulation method with Computer Modeling Group (CMG) STARS simulator. The study was carried out by observing at the pressure, injection rate, and polymer concentration on increasing field recovery factor. This study used cartesian grid with the assumption of homogeneous reservoir, there are no faults or other geological condition in the reservoir, and driving mechanism is only solution gas drive. This reservoir, oil type is light oil with API gravity 40.3˚API and layer of conglomerate rock. The simulation result performed with various scenarios provides a good result. Where the conditions case base case field recovery factor of 6.7%, and after water flooding produced 25.5% of oil, whereas with tertiary recovery method is polymer flooding was carried out with four concentrations of 640 ppm, 1,500 ppm, 3,000 ppm, and 4,000 ppm obtained optimum values at 4,000 ppm polymer concentration with recovery factor 28.9%, SOR reduction final value 0,5255, polymer adsorption of 818,700 ppm, reservoir final pressure 1,707 psi, and an increase in water viscosity to 0.94 cP.


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