Hasil Pencarian  ::  Simpan CSV :: Kembali

"Ketebalan dan porositas reservoar merupakan dua parameter yang krusial dalam perhitungan cadangan minyak atau gas di suatu lapangan. Namun, data seismik yang tersedia dibatasi oleh resolusi vertikal yang sulit untuk mengkarakterisasi reservoar yang bervariasi. Menurut Brown (2009), terdapat dua limit resolusi vertikal data seismik, yaitu limit separabilitas dan limit visibilitas. Limit separabilitas merupakan ketebalan minimum reservoar yang dapat dipisahkan oleh dua wiggle seismik yang biasanya mencapai 1/4 dari panjang gelombang. Pada kondisi ini disebut dengan kondisi tuning. Limit visibilitas merupakan reservoar tertipis yang dapat dilihat oleh amplitudo seismik yang dalam kondisi yang baik dapat mencapai 1/30 dari panjang gelombang. Dengan adanya teori tersebut, peneliti melihat adanya peluang untuk meresolusi seismik di bawah tuning thickness-nya. Penelitian ini dilakukan dengan mengkombinasikan data sumur dan data seismik melalui kalibrasi statistical tuning chart dan model Amplitude Tuning - Porosity*Thickness. Data seismik yang digunakan adalah berupa ekstraksi amplitudo dan isochrone serta analisis frekuensinya. Dengan cara ini, kita dapat meningkatkan resolusi vertikal hingga mendekati limit visibilitas data seismik. Hasil dari penelitian ini berupa peta ketebalan dan peta porosity-thickness dalam domain kedalaman yang sudah terkalibrasi sumur. Lebih dari itu, analisis sedimentologi akan dipadukan guna mengevaluasi peta tersebut agar sesuai dengan fasies sedimennya. Selain itu, peneliti juga mensimulasikan perhitungan volumetrik gas pada reservoar. Pada akhirnya, peta ketebalan yang dihasilkan diharapkan dapat mengurangi ketidakpastian dalam perhitungan cadangan yang nantinya akan mempengaruhi keekonomian lapangan.

---

Reservoir thickness and porosity are two crucial parameters in calculating oil or gas reserves in a field. However, available seismic data is limited by vertical resolution that makes it difficult to characterize the reservoir's variability. According to Brown (2009), there are two limits to the vertical resolution of seismic data, namely the separability limit and the visibility limit. The separability limit is the minimum reservoir thickness that can be separated by two seismic wiggles which usually reaches 1/4 of the wavelength. This phenomenon is called tuning condition. The visibility limit is the thinnest reservoir that can be seen by seismic amplitude which in good conditions can reach 1/30 of the wavelength. With this theory, researchers see an opportunity to resolve resolution below the tuning thickness. This research was carried out by combining well data and seismic data through statistical tuning chart calibration and the Amplitude Tuning - Porosity*Thickness model. The seismic data used is in the form of amplitude and isochrone extraction and frequency analysis. In this way, we can increase the vertical resolution to close to the visibility limit of seismic data. The results of this research are thickness maps and porosity-thickness maps in depth domain. Moreover, sedimentological analyses are integrated to evaluate the map to match the sedimentary facies. Apart from that, researchers also simulated gas volumetric calculations in the reservoir. In the end, the resulting thickness map is expected to reduce uncertainty in reserve calculations which will later affect field economics."

"Bendungan Cabean merupakan salah satu proyek Kementerian PUPR. Bendungan ini merupakan tipe bendungan serbaguna dengan fungsi untuk mengairi daerah irigasi, pengendalian banjir, pembangkit listrik, pariwisata, ketahanan air, dan ketahanan pangan di Kabupaten Blora. Lokasi area rencana pembangunan bendungan di daerah Cabean, Kecamatan Todanan, Kabupaten Blora, Jawa Tengah. Di daerah penelitian ini, telah dilakukan akuisisi data resistivitas dan data bor. Data resistivitas dan data bor digunakan sebagai data sekunder. Pada penelitian ini, penulis mengidentifikasi area dan kedalaman lapisan keras di bawah permukaan tanah dengan menggunakan metode geolistrik dan data bor untuk menentukan jenis fondasi yang dapat digunakan. Akuisisi data resistivitas dilakukan dengan membuat empat lintasan besar, yang mana masing-masing lintasan memiliki panjang 240 m. Hasil akhir dari pengolahan ini adalah persebaran nilai resistivitas batuan di bawah permukaan. Lintasan 1 – 4 memiliki sebaran nilai resistivitas yang beragam, dengan kisaran nilai di antara 2,7 Ωm hingga >579 Ωm. Nilai resistivitas di area penelitian cenderung lebih rendah dikarenakan lokasi penelitian berada di area persawahan. Area ini memiliki banyak vegetasi dan juga irigasi, sehingga banyak air yang tersebar ke dalam lapisan tanah. Selanjutnya, dilakukan korelasi antara data resistivitas dengan data bor. Melalui korelasi data resistivitas dan data bor, dapat dilakukan identifikasi lapisan tanah keras yang mengacu pada SNI 1726:2019. Litologi utama pada area penelitian ini adalah residual soil pada kedalaman 0 – 5 m yang dikategorikan sebagai lapisan tanah sedang – keras, dan perselingan batupasir-batulanau-batulempung pada kedalaman > 5 m yang dikategorikan sebagai lapisan tanah keras. Oleh karena itu, jenis fondasi tanah keras yang digunakan berdasarkan kedalamannya adalah jenis fondasi tiang pancang atau fondasi bored pile.

---

The Cabean Dam is one of the projects undertaken by the Ministry of Public Works and Housing (PUPR). This dam is a multifunctional type, serving purposes such as irrigation, flood control, electricity generation, tourism, water security, and food security in Blora Regency. The planned construction site of the dam is located in Cabean, Todanan Subdistrict, Blora Regency, Central Java. In this research area, resistivity data and borehole data have been acquired. Resistivity data are used as primary data, while borehole data are used as secondary data. In this study, the author identifies the area and depth of the hard layer beneath the ground surface using geoelectrical methods and borehole data to determine the type of foundation that can be utilized. The acquisition of resistivity data was conducted by creating four major traverses, each consisting of several minor traverses, and complemented by ten borehole data points. The final result of this processing is the distribution of subsurface rock resistivity values. Traverses 1 to 4 have a diverse range of resistivity values, ranging from 2.7 Ωm to >579 Ωm. The resistivity values in the research area tend to be lower because the location is in a rice field area. This area has abundant vegetation and irrigation, causing a significant amount of water to infiltrate into the soil layers. Subsequently, a correlation was made between the resistivity data and the borehole data. Through the correlation of resistivity and borehole data, the identification of the hard soil layer in accordance with SNI 1726:2019 can be conducted. The main lithology in this research area is residual soil at a depth of 0 – 5 meters, categorized as a medium-hard soil layer, and interbedded sandstone-siltstone- claystone at a depth of > 5 meters, categorized as a hard soil layer. Therefore, the type of hard soil foundation used based on its depth is either a pile foundation or a bored pile foundation."

"Inversi Seismik merupakan metoda untuk mendapatkan gambaran model geologi bawah permukaan dengan menggunakan data seismik sebagai data input utama dan data sumur sebagai kontrolnya. Hasil yang didapat dari metoda inversi adalah informasi yang terkandung di dalam lapisan batuan berupa impedansi (akustik atau elastik). Hasilnya berkorelasi secara kuantitatif terhadap parameter fisik pada reservoir yang terukur pada sumur, salah satunya adalah porositas. Maksud dari penelitian ini adalah bahwa penulis akan melakukan contoh pemodelan inversi AI pada reservoar di Lapangan IWR, sedangkan tujuannya adalah untuk mengestimasi porositas reservoar di daerah interest melalui pendekatan inversi seismik AI tersebut. Diharapkan nantinya dapat menentukan usulan sumur pemboran beserta justifikasinya dan memungkinkan untuk di eksplorasi lebih lanjut. Hasil penelitian yang diharapkan dari studi ini adalah bahwa penulis mampu mengintegrasikan data porositas dari beberapa sumur yang ada terhadap data seismik atribut dengan pemodelan inversi AI.

---

Seismic Inversion is a method to gain a subsurface geological model with seismic data as a main input and well log data as a controller. The result of this method is a brief description about lithological impedance (acoustic or elastic). This informations are quantitatively correlable with another physical parameter on reservoar, e.g. porosity.

The aims of this study is doing a seismic inversion AI modelling on Field IWR, and the goal is estimating the reservoir porosity at the interest zone with previous inversion result.

Finally we can propose some wells with its justifications and able for further explorations. Expectation of the study is author able to integrate the porosity data of many wells into seismic attribute data with seismic inversions AI, which it can be useful for estimating reservoir porosity at other zone."

"Analisis petrofisika dilakukan untuk mendapatkan parameter-parameter petrofisika seperti kandungan lempung, porositas dan saturasi air, yang berguna untuk karakterisasi batuan reservoar. Berdasarkan data sumur 17 dan 50, Reservoar yang akan diteliti berada pada kedalaman 3328.50 hingga 3469 feet yang merupakan formasi missisauga tengah yang batuannya didominasi oleh batuan pasir. Dari perhitungan analisis petrofisika, didapatkan nilai kandungan lempung berkisar antara 13%-36%, porositas berkisar antara 16%-23% dan saturasi air berkisar antara 39%-53%. Analisis petrofisika hanya mampu memberikan informasi tentang karakter reservoar secara vertikal. Untuk itu itu perlu dilakukan analisis multiatribut seismik. Dengan analisis mulitatribut seismik persebaran parameter petrofisika seperti kandungan lempung, porositas dan saturasi air pada volum seismik bisa didapatkan. Atribut yang digunakan adalah sampled-based attributes dan inversi seismik sebagai eksternal atribut. Penggunaan Neural network dapat meningkatkan korelasi antara nilai log prediksi dengan nilai log sebenarnya hingga mencapai nilai 0.98.

---

Analysis petrophysical result can provide vertical information about the character of the reservoir. However, this method lacking in the horizontal resolution. so we can provide 3D information from analysis multiatribut. Shaly sand rock in Norwegia field is an area that has potential as a reservoir. Petrophysical parameters that will be studied in this thesis, such as clay content, porosity and water saturation. From the petrophysical analysis calculation , the value obtained clay content ranged from 13%-36%, porosity ranged from 16%-23% and a water saturation ranged from 39%-53%. Petrophysical parameters throughout the seismic volume will be predicted using multiatribut analysis. Linear sparse spike inversion results will be used as an external atribute on multiatribut analysis. The use of Neural Network aims to improve the correlation between the log predictive value with the actual value . Results from the log input will be spread throughout the seismic volume to get a pseudo volume."

"ABSTRAK:Dalam eksplorasi minyak dan gas bumi, penentuan lokasi keberadaan cekungan (basin) sangat penting untuk diketahui. Hal ini dikarenakan cekungan (basin) berkaitan erat dengan lingkungan pembentukan batuan induk (source rock). Telah dilakukan pengukuran survei gayaberat pada daerah cekungan Sumatera Selatan. Tujuan dilakukannya pengukuran ini adalah untuk mengetahui daerah-daerah yang diduga merupakan cekungan (basin) sebagai tempat pembentukan source rock. Pada nilai anomali Bouguer yang didapatkan dari hasil pengukuran selanjutnya dilakukan analisa spektrum untuk membantu mendapatkan model basement cekungan. Pada analisa lebih lanjut, dilakukan pemisahan anomali regional dan residual menggunakan metode Moving Average dan metode Polinomial Trend Surface Analysis untuk mengetahui daerah zona cekungan. Analisa First Derivative dilakukan untuk mengetahui daerah zona struktur patahan pada cekungan. Pada proses pemodelan 2D Forward Modelling, digunakan data sumur, hasil spektrum analisis berupa model kedalaman, peta geologi dan kurva FHD sebagai acuan dalam pemodelan. Hasil dari pemodelan 2D Forward Modelling menunjukkan adanya cekungan dengan kedalaman basement berkisar 2000 m sampai 3000 m. Interpretasi terpadu dari metode pengolahan data gayaberat yang dilakukan didapatkan keberadaan cekungan yang memanjang dari arah Baratlaut ke Tenggara-Selatan.

---

ABSTRACT:In oil and gas exploration, determining the location of the basin is very important to be known. It is because the basin is closely related to the formation of the host rock environment (source rock). Geophysical survey using gravity method has been on the South Sumatra basin area. The purpose of this measurement is to determine the areas that are considered basin as the source rock formation. On the value Bouguer anomaly obtained from the results of measurements of the spectral analysis is performed to help get the model basin basement. On further analysis, the separation of regional and residual anomalies using the Moving Average method and Polynomial Trend Surface Analysis method to determine the zone of the basin area. First Derivative analysis was conducted to determine the structure of the fault zone area in the basin. In the modeling process 2D Forward Modeling, used well data, the results of spectral analysis of a model of depth, geological maps and FHD curve as a reference in the modeling. Results of Forward Modelling 2D modeling shows basin with depths ranging from 2000 m to the basement of 3000 m. Integrated interpretation of gravity data processing method conducted found the existence of the basin that extends from the North West to South - East."

"Tesis ini meneliti tentang persepsi jarak baik pada lingkungan nyata maupun maya dalam jarak exocentric pada ruang peri-personal. Sepuluh partisipan melakukan 72 estimasi jarak antara 10 sampai dengan 50 cm, pada enam tata letak sasaran yang berbeda dan juga dikombinasikan dengan tiga parallax yang berbeda. Penelitian ini dilakukan dengan mengkombinasikan dua macam target, maya dan nyata yang dilihat dengan menggunakan kacamata tiga dimensi. Hasil penelitian menunjukkan bahwa terjadi kompresi atau penurunan estimasi jarak pada ruang peri-personal dalam jarak exocentric yang mengkombinasikan antara dua macam target, maya dan nyata. Hasil tersebut berbeda dari penelitian sebelumnya pada jarak egocentric dalam ruang peri-personal yang sama. Hal yang menarik dari penelitian ini adalah hasil yang konsisten dengan penelitian yang dilakukan oleh peneliti sebelumnya dengan menggunakan teknologi High Mounted Display (HMD), khususnya permasalahan kesalahan pada bidang pandang, ketika kita menempatkan target atau objek nyata pada bagian bawah terhadap objek lainnya, yaitu terjadi penurunan estimasi jarak. Meskipun hasil yang kita dapatkan konsisten dengan penelitian sebelumnya, penyebab mengapa hal ini terjadi masih belum dapat diketahui. Dengan memahami permasalahan ini seharusnya dapat memberikan perbaikan yang lebih baik kedepannya di bidang teknologi maya. Meskipun demikian, pada penelitian ini berdasarkan metode ANOVA yang kita lakukan, teknik bagaimana kita menempatkan sasaran baik nyata maupun maya (tata letak) mempengaruhi akurasi dari estimasi jarak, F(5,45) = 7.285 dengan p< .05, dan, parallax juga mempengaruhi akurasi dari estimasi jarak F(2,18) =4.934 dengan p = 0.02.

---

The present study investigated distance perception both in virtual and real environments within exocentric distance at peri-personal space. Ten participants estimated 72 target distances between 10 cm and 50 cm in six different target positions combined with three different parallaxes. The study examined virtual targets seen through the 3D glasses, and combined real and virtual objects. The results give evidence that the exocentric distance of virtual and combined real and virtual objects is underestimated at peri-personal distance, a different result from a previous cross study that has been found in egocentric distance in the same peri- personal space. The interesting aspect of this finding is that our result is consistent with a previous study, regarding the implication of a misleading field of view when real object placed in lower side. This result indicates the same degree of underestimation when showed both the real + virtual environments with HMD technology. Although, the results show that participants underestimated the distance for exocentric within peri-personal space, the reason why this happened remains unknown. Understanding these issues should lead to useful and applicable virtual reality technology improvement. However, the ANOVA result shows that the way we positioned a real and virtual target (layout) is affecting the accuracy of estimation, F(5,45) = 7.285 and p < .05, while, the parallax also has effect on the accuracy of distance estimation F(2,18) = 4.934 and p = 0.02."

"[ABSTRAK Lapangan-X merupakan lapangan gas di Cekungan Kutai yang dikembangkan sejak tahun 1986. Reservoar lapangan-X merupakan endapan delta Miosen akhir yang berlapis, dimana dikarakterisasikan oleh formasi yang didominasi oleh lempung. Perselingan antara batupasir dan batuserpih menghasilkan heterogenitas porositas yang cukup tinggi. Salah satu metode yang efektif dalam mengatasi tingkat heterogenitas yang tinggi adalah dengan metode Artificial Neural Network (ANN). ANN menggunakan algoritma Probabilistic Neural Network (PNN) mampu mendiskriminasikan daerah yang memiliki sebaran porositas yang tinggi dan rendah dengan baik pada zona Fresh Water Sand (FWS) lapangan-X dibanding dengan metode Multiatribut linier yang cenderung merupakan nilai sebaran porositas rata-rata. Nilai korelasi hasil prediksi terhadap target menggunakan metode PNN mencapai 0.8610 dengan rata-rata kesalahan (average error) sebesar 0.0283, sementara nilai korelasi hasil metode Multiatribut linier hanya sebesar 0.7098 dengan rata-rata kesalahan (average error) sebesar 0.0398. Hasil PNN pada sayatan waktu +10 ms dari horizon FS33 berhasil mengkarakterisasikan sebaran porositas batupasir yang bersih dari lempung di bagian selatan daerah penelitian, dimana fasies pengendapan batupasir tersebut diinterpretasikan berasal dari dataran delta. Sementara sayatan waktu -10 ms dari horizon FS42, menunjukan sebaran porositas batugamping dengan fasies pengendapannya diinterpretasikan berasal dari lingkungan neritik (shelf). Dari penelitian ini, dapat disimpulkan bahwa metode PNN berhasil menggambarkan sebaran porositas batuan di zona Fresh Water Sand (FWS) lapangan-X dengan baik sehingga hasil prediksi penyebaran yang dilakukan mampu mendekati data- data sumuran.

---

ABSTRACT X-field is a gas field in Kutai Basin and it has been developed since 1986. Reservoir of X-field is a multi layered upper Miocene deltaic deposits and characterized by a shaly formation. A highly intercalation between sand & shale unit in X-field has been contributed to the heterogeneity of porosity in the area. One of the effective methods to spatially quantify such heterogeneity of porosity is by using Artificial Neural Networks (ANN). ANN with Probability Neural Network (PNN) algorithm has been successfully retained more dynamic range, high and low frequency porosity content, compare to the Multiattributes linear which is tend to show a smoothed, or more averaged prediction. The correlation value from PNN methods can be up to 0.8610 with average error is 0.0283, while correlation value from Multiattribute linear only up to 0.7098 with average error is 0.0398. The time slice of PNN result at +10ms from horizon FS33 has been clearly figured out an accumulation of high porosity in the southern area of the interval target which is indicated as a clean sand lithology based on sensitivity analysis. And such accumulation has formed a distributaries channel trend which is interpreted as delta plain deposits. Meanwhile, the time slice of PNN result at - 10 ms from horizon FS42 has indicated a carbonate lithology which is interpreted as shelf deposits. From this study, it?s concluded that PNN algorithm as a nonlinear function has been successfully showed a better porosity distribution in the Fresh Water Sand (FWS) zone of X-field.;X-field is a gas field in Kutai Basin and it has been developed since 1986. Reservoir of X-field is a multi layered upper Miocene deltaic deposits and characterized by a shaly formation. A highly intercalation between sand & shale unit in X-field has been contributed to the heterogeneity of porosity in the area. One of the effective methods to spatially quantify such heterogeneity of porosity is by using Artificial Neural Networks (ANN). ANN with Probability Neural Network (PNN) algorithm has been successfully retained more dynamic range, high and low frequency porosity content, compare to the Multiattributes linear which is tend to show a smoothed, or more averaged prediction. The correlation value from PNN methods can be up to 0.8610 with average error is 0.0283, while correlation value from Multiattribute linear only up to 0.7098 with average error is 0.0398. The time slice of PNN result at +10ms from horizon FS33 has been clearly figured out an accumulation of high porosity in the southern area of the interval target which is indicated as a clean sand lithology based on sensitivity analysis. And such accumulation has formed a distributaries channel trend which is interpreted as delta plain deposits. Meanwhile, the time slice of PNN result at - 10 ms from horizon FS42 has indicated a carbonate lithology which is interpreted as shelf deposits. From this study, it?s concluded that PNN algorithm as a nonlinear function has been successfully showed a better porosity distribution in the Fresh Water Sand (FWS) zone of X-field.;X-field is a gas field in Kutai Basin and it has been developed since 1986. Reservoir of X-field is a multi layered upper Miocene deltaic deposits and characterized by a shaly formation. A highly intercalation between sand & shale unit in X-field has been contributed to the heterogeneity of porosity in the area. One of the effective methods to spatially quantify such heterogeneity of porosity is by using Artificial Neural Networks (ANN). ANN with Probability Neural Network (PNN) algorithm has been successfully retained more dynamic range, high and low frequency porosity content, compare to the Multiattributes linear which is tend to show a smoothed, or more averaged prediction. The correlation value from PNN methods can be up to 0.8610 with average error is 0.0283, while correlation value from Multiattribute linear only up to 0.7098 with average error is 0.0398. The time slice of PNN result at +10ms from horizon FS33 has been clearly figured out an accumulation of high porosity in the southern area of the interval target which is indicated as a clean sand lithology based on sensitivity analysis. And such accumulation has formed a distributaries channel trend which is interpreted as delta plain deposits. Meanwhile, the time slice of PNN result at - 10 ms from horizon FS42 has indicated a carbonate lithology which is interpreted as shelf deposits. From this study, it’s concluded that PNN algorithm as a nonlinear function has been successfully showed a better porosity distribution in the Fresh Water Sand (FWS) zone of X-field., X-field is a gas field in Kutai Basin and it has been developed since 1986. Reservoir of X-field is a multi layered upper Miocene deltaic deposits and characterized by a shaly formation. A highly intercalation between sand & shale unit in X-field has been contributed to the heterogeneity of porosity in the area. One of the effective methods to spatially quantify such heterogeneity of porosity is by using Artificial Neural Networks (ANN). ANN with Probability Neural Network (PNN) algorithm has been successfully retained more dynamic range, high and low frequency porosity content, compare to the Multiattributes linear which is tend to show a smoothed, or more averaged prediction. The correlation value from PNN methods can be up to 0.8610 with average error is 0.0283, while correlation value from Multiattribute linear only up to 0.7098 with average error is 0.0398. The time slice of PNN result at +10ms from horizon FS33 has been clearly figured out an accumulation of high porosity in the southern area of the interval target which is indicated as a clean sand lithology based on sensitivity analysis. And such accumulation has formed a distributaries channel trend which is interpreted as delta plain deposits. Meanwhile, the time slice of PNN result at - 10 ms from horizon FS42 has indicated a carbonate lithology which is interpreted as shelf deposits. From this study, it’s concluded that PNN algorithm as a nonlinear function has been successfully showed a better porosity distribution in the Fresh Water Sand (FWS) zone of X-field.]"

"ABSTRAKJakarta sebagai ibu kota negara memiliki permasalahan. Kanal Banjir Timur dibangun sebagai jawaban permasalahan banjir Jakarta. Kanal Banjir Timur mengalirkan debit dari lima sungai yang masuk ke wilayah Jakarta. Permasalahan kemacetan juga merupakan permasalahan yang harus diselesaikan. Dimensi Kanal Banjir Timur memiliki potensi sebagai prasarana pelayaran barang guna mengurangi kemacetan yang ada. Sebagai prasarana pelayaran diperlukan aliran yang memenuhi persyaratan kedalaman aliran minimum dan kecepatan aliran maksimum saluran pelayaran. Perhitungan kedalaman aliran minimum dihitung dengan debit andalan periode ulang dua tahun. Perhitungan kecepatan aliran maksimum dihitung dengan debit banjir bulanan periode ulang dua tahun. Periode ulang dua tahun dipilih untuk menentukan tipikal fluktuasi debit bulanan setiap tahunnya karena akan digunakan sebagai pertimbangan operasional pelayaran. Rentang waktu antara kedalaman aliran minimum dengan kecepatan aliran maksimum menjadi rentang waktu efektif pelayaran.

---

ABSTRACT

Jakarta as the national capital has many problems such as flooding and transportation. The East Flood Canal was built to decrease the impact of Jakarta flood. The canal drains discharge from five rivers that flow through Jakarta to the sea. The canal from its master plan aspect has the potential as a shipping infrastructure for reducing existing congestion. Shipping infrastructure has to have minimum flow depth and maximum flow speed requirements of shipping channel. Minimum depth calculation is calculated by mainstay discharge using two-year return period. The calculation of maximum flow velocity is calculated by monthly dependable flow discharge for a two-year return period. A two-year return period was chosen to determine the typical daily fluctuation of discharge to be used as a consideration of shipping operational. Time window between minimum flow height and maximum flow velocity will be the time window of effective shipping operational. "

"The concentration of methana (CH4) in the atmosphere is increasing at 1% per annum and rice paddies are one of the sources that contrubute to about atmospheric CH4...."