(1. 湖南科技大學(xué) 頁(yè)巖氣資源利用湖南重點(diǎn)實(shí)驗(yàn)室，湘潭 411201；
2. 中南大學(xué) 地球科學(xué)與信息物理學(xué)院，長(zhǎng)沙 410083；
3. 湖南科技大學(xué) 資源環(huán)境與安全工程學(xué)院，湘潭 411201)
摘 要: 針對(duì)在重力梯度張量正演中計(jì)算耗時(shí)過(guò)長(zhǎng)和核矩陣內(nèi)存消耗過(guò)大等制約反演實(shí)施的瓶頸問(wèn)題，在L1范數(shù)的基礎(chǔ)上，引入種植反演，用累加求和分析替換迭代求解，避免計(jì)算或存儲(chǔ)反演核矩陣，以減少內(nèi)存占用和加快反演迭代；針對(duì)種植反演容易導(dǎo)致相鄰異常源相互侵入的問(wèn)題，引入一個(gè)基于位場(chǎng)水平衰減特性加權(quán)函數(shù)來(lái)限制密度吸引子的作用范圍，以期使密度吸引子忽略較遠(yuǎn)的異常源，抑制相鄰異常源相互干擾。反演結(jié)果及分析表明重力及重力梯度張量種植反演所需計(jì)算機(jī)內(nèi)存小和水平衰減特性加權(quán)函數(shù)能有效的抑制相鄰異常源的侵入。
關(guān)鍵字: 種植反演；水平加權(quán)特性函數(shù)；重力梯度張量；L1范數(shù)
（1. Hunan Provincial Key Laboratory of Shale Gas Resource Utilization, Hunan University of Science and Technology, Xiangtan 411201, China;
2. School of Geosciences and Info-physics, Central South University, Changsha 410083, China;
3. School of Resource Environment and Safety Engineering, Hunan University of Science and Technology, Xiangtan 411201, China）
Abstract:Large-scale inversion of gravity gradient tensor data is a time-consuming problem with high demands on computational and physical memory usage. To avoid extraordinary matrix-vector multiplications in each inverse iteration and to speed up the forward of geophysical models, planting inversion is introduced and conjugate gradient iteration replaced by accumulation summary based on L1 norm. The planting inversion easily leads to adjacent anomalies mutually invasive, a horizontal weighted function is proposed to suppress mutual interference between the adjacent anomaly sources. These results of the inversions and analysis results show that planting inversion with horizontal weighted function obtain a meaningful geophysical model. And these methods require little memory and high efficiency.
Key words: planting inversion; horizontal weighted function; gravity gradient tensor; L1 norm
