| Sequence Stratigrapyh has been used widely in the exploration and development of the oil field. It has important significance to strengthen the research of the sequence stratigraphy method for increasing the success of the drilling of the oil field. The purpose of the paper is to study the sequence stratigraphy using Maximum Entropy Spectral Analysis Method of wireline logs. The key method is to analysis the wireline logs using Maximum Entropy Spectral Analysis Method based on the Maximum Entropy method. According to varies purpose, the wireline logs containing complicated spectral attribute content are decomposted to the wireline logs making up simple waves by a sliding window technique, and then PEFA curve is obtained. Discontinuity (sequence stratigraphy boundaries) could be identified rapidly through analysing the PEFA curve. The INPEFA curve is more value than PEFA curve, the INPEFA curve is computed from the PEFA values by a numerical integration. We can identify the sequence stratigraphy boundaries and flooding surface boundaries utilizing INPEFA curve turning-point. The trend of INPEFA curve reflects different geological meaning, a positive trend (from left to right) shows a change of the climate from dry to wet, water from shallow to deep, sediment from coarse to fine. a negative trend (from right to left) of INPEFA represents a change of the climate from wet to dry, water from deep to shallow, sediment from fine to coarse. In the course of the applying INPEFA, firstly, a long term INPEFA curve is generated from the top to bottom of the whole well and the low frequency sequence are identified. Secondly, a short term INPEFA curve is generated according to the research goal and the high frequency sequence can be identified, and then a sequence stratigraphy framework is builded up. Thirdly, the division and correlation of the reservoirs is conducted under the control of the sequence stratigraphy framework accurately and the connectivity of sand body can be judged. The paper analyses various wireline logs, which applies Maximum Entropy Spectral Analysis Method, the results show that applying INPEFA curve can identify Milankovitch cycle; applying GR-INPEFA curve can identify sedimentary cycle; applying SP-INPEFA curve can identify parasequence; applying AC-INPEFA, GR-INPEFA curve can recognize sequence stratigraphy boundaries; applying RA-INPEFA, GR-INPEFA, AC-INPEFA curve can recognize flooding surface. The research processes the practical data of the typical siliciclastic sand body and gets satisfatory effect. Delta reservoir of Sheng er region in ShengLi oil field and the beach bar lithologic reservoir of DaWangBei region in ShengLi oil field has been studied in details by applying Maximum Entropy Spectral Analysis Method, compared with the research results which applying other geological approaches gets, it shows a satisfactory practical applied effect. Based on what has been discussed above, the conclusion is safely drawn: (1) Applying Maximum Entropy Spectral Analysis Method abstracts the spectral attribute from complicated and varied logging data and builds up relevant pattern, which reduces the artificial influence by using original logging data when we study the sequence stratigraphy and improves the resolution of the logging data compared with the traditional geological approaches. (2) We can find out the geological information hidden the logging data and identify the sequence stratigraphy boundaries, sedimentary cycle, the hierarchy of the sequence boundaries rapidly. (3) In the regions without other data, we can take advantage of logging data which has the advantage of high resolution in the vertical and numerous data to conduct the research of the sequence stratigraphy by applying Maximum Entropy Spectral Analysis Method. (4) In the course of processing practical data, we should select the different logging succession according to different geological situation and the data quality. We should take different research measures in order to achieve a satisfactory effect. |
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