scholarly journals Accelerated soil development due to seasonal water-saturation under hydric conditions

Geoderma ◽  
2021 ◽  
Vol 401 ◽  
pp. 115328
Author(s):  
Zoltán Szalai ◽  
Marianna Ringer ◽  
Tibor Németh ◽  
Péter Sipos ◽  
Katalin Perényi ◽  
...  
Author(s):  
A. Syahputra

Surveillance is very important in managing a steamflood project. On the current surveillance plan, Temperature and steam ID logs are acquired on observation wells at least every year while CO log (oil saturation log or SO log) every 3 years. Based on those surveillance logs, a dynamic full field reservoir model is updated quarterly. Typically, a high depletion rate happens in a new steamflood area as a function of drainage activities and steamflood injection. Due to different acquisition time, there is a possibility of misalignment or information gaps between remaining oil maps (ie: net pay, average oil saturation or hydrocarbon pore thickness map) with steam chest map, for example a case of high remaining oil on high steam saturation interval. The methodology that is used to predict oil saturation log is neural network. In this neural network method, open hole observation wells logs (static reservoir log) such as vshale, porosity, water saturation effective, and pay non pay interval), dynamic reservoir logs as temperature, steam saturation, oil saturation, and acquisition time are used as input. A study case of a new steamflood area with 16 patterns of single reservoir target used 6 active observation wells and 15 complete logs sets (temperature, steam ID, and CO log), 19 incomplete logs sets (only temperature and steam ID) since 2014 to 2019. Those data were divided as follows ~80% of completed log set data for neural network training model and ~20% of completed log set data for testing the model. As the result of neural model testing, R2 is score 0.86 with RMS 5% oil saturation. In this testing step, oil saturation log prediction is compared to actual data. Only minor data that shows different oil saturation value and overall shape of oil saturation logs are match. This neural network model is then used for oil saturation log prediction in 19 incomplete log set. The oil saturation log prediction method can fill the gap of data to better describe the depletion process in a new steamflood area. This method also helps to align steam map and remaining oil to support reservoir management in a steamflood project.


2020 ◽  
pp. 28-34
Author(s):  
I.S. Putilov ◽  
◽  
I.P. Gurbatova ◽  
S.V. Melekhin ◽  
M.S. Sergeev ◽  
...  

Author(s):  
K.V. Kovalenko ◽  
◽  
M.S. Khokhlova ◽  
A.N. Petrov ◽  
N.I. Samokhvalov ◽  
...  

2017 ◽  
Vol 54 (3) ◽  
pp. 181-201
Author(s):  
Rebecca Johnson ◽  
Mark Longman ◽  
Brian Ruskin

The Three Forks Formation, which is about 230 ft thick along the southern Nesson Anticline (McKenzie County, ND), has four “benches” with distinct petrographic and petrophysical characteristics that impact reservoir quality. These relatively clean benches are separated by slightly more illitic (higher gamma-ray) intervals that range in thickness from 10 to 20 ft. Here we compare pore sizes observed in scanning electron microscope (SEM) images of the benches to the total porosity calculated from binned precession decay times from a suite of 13 nuclear magnetic resonance (NMR) logs in the study area as well as the logarithmic mean of the relaxation decay time (T2 Log Mean) from these NMR logs. The results show that the NMR log is a valid tool for quantifying pore sizes and pore size distributions in the Three Forks Formation and that the T2 Log Mean can be correlated to a range of pore sizes within each bench of the Three Forks Formation. The first (shallowest) bench of the Three Forks is about 35 ft thick and consists of tan to green silty and shaly laminated dolomite mudstones. It has good reservoir characteristics in part because it was affected by organic acids and received the highest oil charge from the overlying lower Bakken black shale source rocks. The 13 NMR logs from the study area show that it has an average of 7.5% total porosity (compared to 8% measured core porosity), and ranges from 5% to 10%. SEM study shows that both intercrystalline pores and secondary moldic pores formed by selective partial dissolution of some grains are present. The intercrystalline pores are typically triangular and occur between euhedral dolomite rhombs that range in size from 10 to 20 microns. The dolomite crystals have distinct iron-rich (ferroan) rims. Many of the intercrystalline pores are partly filled with fibrous authigenic illite, but overall pore size typically ranges from 1 to 5 microns. As expected, the first bench has the highest oil saturations in the Three Forks Formation, averaging 50% with a range from 30% to 70%. The second bench is also about 35 ft thick and consists of silty and shaly dolomite mudstones and rip-up clast breccias with euhedral dolomite crystals that range in size from 10 to 25 microns. Its color is quite variable, ranging from green to tan to red. The reservoir quality of the second bench data set appears to change based on proximity to the Nesson anticline. In the wells off the southeast flank of the Nesson anticline, the water saturation averages 75%, ranging from 64% to 91%. On the crest of the Nesson anticline, the water saturation averages 55%, ranging from 40% to 70%. NMR porosity is consistent across the entire area of interest - averaging 7.3% and ranging from 5% to 9%. Porosity observed from samples collected on the southeast flank of the Nesson Anticline is mainly as intercrystalline pores that have been extensively filled with chlorite clay platelets. In the water saturated southeastern Nesson Anticline, this bench contains few or no secondary pores and the iron-rich rims on the dolomite crystals are less developed than those in the first bench. The chlorite platelets in the intercrystalline pores reduce average pore size to 500 to 800 nanometers. The third bench is about 55 ft thick and is the most calcareous of the Three Forks benches with 20 to 40% calcite and a proportionate reduction in dolomite content near its top. It is also quite silty and shaly with a distinct reddish color. Its dolomite crystals are 20 to 50 microns in size and partly abraded and dissolved. Ferroan dolomite rims are absent. This interval averages 7.1% porosity and ranges from 5% to 9%, but the pores average just 200 nanometers in size and occur mainly as microinterparticle pores between illite flakes in intracrystalline pores in the dolomite crystals. This interval has little or no oil saturation on the southern Nesson Anticline. Unlike other porosity tools, the NMR tool is a lithology independent measurement. The alignment of hydrogen nuclei to the applied magnetic field and the subsequent return to incoherence are described by two decay time constants, longitudinal relaxation time (T1) and transverse relaxation time (T2). T2 is essentially the rate at which hydrogen nuclei lose alignment to the external magnetic field. The logarithmic mean of T2 (T2 Log Mean) has been correlated to pore-size distribution. In this study, we show that the assumption that T2 Log Mean can be used as a proxy for pore-size distribution changes is valid in the Three Forks Formation. While the NMR total porosity from T2 remains relatively consistent in the three benches of the Three Forks, there are significant changes in the T2 Log Mean from bench to bench. There is a positive correlation between changes in T2 Log Mean and average pore size measured on SEM samples. Study of a “type” well, QEP’s Ernie 7-2-11 BHD (Sec. 11, T149N, R95W, McKenzie County), shows that the 1- to 5-micron pores in the first bench have a T2 Log Mean relaxation time of 10.2 msec, whereas the 500- to 800-nanometer pores in the chlorite-filled intercrystalline pores in the second bench have a T2 Log Mean of 4.96 msec. This compares with a T2 Log Mean of 2.86 msec in 3rd bench where pores average just 200 nanometers in size. These data suggest that the NMR log is a useful tool for quantifying average pore size in the various benches of the Three Forks Formation.


Sign in / Sign up

Export Citation Format

Share Document